diff --git a/feature_importance/01_ablation_classification_script.sh b/feature_importance/01_ablation_classification_script.sh
index dbfacea..3865dab 100755
--- a/feature_importance/01_ablation_classification_script.sh
+++ b/feature_importance/01_ablation_classification_script.sh
@@ -4,7 +4,7 @@
#SBATCH --partition=yugroup
source activate mdi
-command="01_run_ablation_classification.py --nreps 1 --config mdi_local.real_data_classification --split_seed ${1} --ignore_cache --create_rmd --result_name Diabetes_classification_parallel"
+command="01_run_ablation_classification.py --nreps 1 --config mdi_local.real_data_classification --split_seed ${1} --ignore_cache --create_rmd --result_name fico"
# Execute the command
python $command
\ No newline at end of file
diff --git a/feature_importance/01_ablation_regression_script.sh b/feature_importance/01_ablation_regression_script.sh
index b5013fe..6686f85 100755
--- a/feature_importance/01_ablation_regression_script.sh
+++ b/feature_importance/01_ablation_regression_script.sh
@@ -4,11 +4,7 @@
#SBATCH --partition=yugroup
source activate mdi
-command="01_run_ablation_regression.py --nreps 1 --config mdi_local.real_data_regression --split_seed ${1} --ignore_cache --create_rmd --result_name diabetes_regression"
+command="01_run_ablation_regression.py --nreps 1 --config mdi_local.real_data_regression --split_seed ${1} --ignore_cache --create_rmd --result_name satellite_image"
# Execute the command
-python $command
-
-
-
-python OLD_XX.py --nreps 1 --config mdi_local.real_data_regression --split_seed ${1} --ignore_cache --create_rmd --result_name diabetes_regression"
\ No newline at end of file
+python $command
\ No newline at end of file
diff --git a/feature_importance/01_run_ablation_classification.py b/feature_importance/01_run_ablation_classification.py
index 8b388b5..adf1199 100644
--- a/feature_importance/01_run_ablation_classification.py
+++ b/feature_importance/01_run_ablation_classification.py
@@ -16,7 +16,7 @@
from collections import defaultdict
from typing import Callable, List, Tuple
import itertools
-from sklearn.metrics import roc_auc_score, f1_score, recall_score, precision_score, mean_squared_error
+from sklearn.metrics import roc_auc_score, f1_score, recall_score, precision_score, mean_squared_error, average_precision_score
from sklearn import preprocessing
from sklearn.ensemble import RandomForestClassifier
from sklearn.linear_model import LogisticRegressionCV
@@ -150,9 +150,10 @@ def compare_estimators(estimators: List[ModelConfig],
# fit model
est.fit(X_train, y_train)
test_all_auc = roc_auc_score(y_test, est.predict_proba(X_test)[:, 1])
- test_all_auprc = auprc_score(y_test, est.predict_proba(X_test)[:, 1])
+ test_all_auprc = average_precision_score(y_test, est.predict_proba(X_test)[:, 1])
test_all_f1 = f1_score(y_test, est.predict_proba(X_test)[:, 1] > 0.5)
+ np.random.seed(42)
indices_train = np.random.choice(X_train.shape[0], 100, replace=False)
indices_test = np.random.choice(X_test.shape[0], 100, replace=False)
X_train_subset = X_train[indices_train]
@@ -183,21 +184,29 @@ def compare_estimators(estimators: List[ModelConfig],
metric_results[f'ablation_seed_{i}'] = seeds[i]
start = time.time()
local_fi_score_train_subset = fi_est.cls(X_train=X_train, y_train=y_train,
- X_test=X_test, y_test=y_test,
- fit=copy.deepcopy(est), data_fit_on="train", **fi_est.kwargs)
- local_fi_score_test = fi_est.cls(X_train=X_train, y_train=y_train,
- X_test=X_test, y_test=y_test,
- fit=copy.deepcopy(est), data_fit_on="test", **fi_est.kwargs)
- local_fi_score_test_subset = None
+ X_train_subset = X_train_subset, y_train_subset=y_train_subset,
+ X_test=X_test, y_test=y_test,
+ fit=copy.deepcopy(est), data_fit_on="train_subset", **fi_est.kwargs)
+ if fi_est.name not in ["LIME_RF_plus", "Kernel_SHAP_RF_plus"]:
+ local_fi_score_test = fi_est.cls(X_train=X_train, y_train=y_train,
+ X_train_subset = X_train_subset, y_train_subset=y_train_subset,
+ X_test=X_test, y_test=y_test,
+ fit=copy.deepcopy(est), data_fit_on="test", **fi_est.kwargs)
+ else:
+ local_fi_score_test = None
+ local_fi_score_test_subset = fi_est.cls(X_train=X_train, y_train=y_train,
+ X_train_subset = X_train_subset, y_train_subset=y_train_subset,
+ X_test=X_test_subset, y_test=y_test_subset,
+ fit=copy.deepcopy(est), data_fit_on="test", **fi_est.kwargs)
end = time.time()
metric_results['fi_time'] = end - start
- feature_importance_list.append(local_fi_score_train_subset)
+ # feature_importance_list.append(local_fi_score_train_subset)
feature_importance_list.append(local_fi_score_test)
feature_importance_list.append(local_fi_score_test_subset)
ablation_models = {"RF_Classifier": RandomForestClassifier(n_estimators=100, min_samples_leaf=1, max_features='sqrt', random_state=42),
- "Logistic": LogisticRegressionCV(),
- "SVM": SVC(probability=True),
+ "LogisticCV": LogisticRegressionCV(random_state=42),
+ "SVM": SVC(random_state=42, probability=True),
"XGBoost_Classifier": xgb.XGBClassifier(random_state=42),
"RF_Plus_Classifier": RandomForestPlusClassifier(rf_model=RandomForestClassifier(n_estimators=100, min_samples_leaf=1, max_features='sqrt', random_state=42))}
@@ -208,7 +217,7 @@ def compare_estimators(estimators: List[ModelConfig],
ablation_est.fit(X_train, y_train)
y_pred = ablation_est.predict_proba(X_train_subset)[:, 1]
metric_results[a_model+'_train_subset_AUROC_before_ablation'] = roc_auc_score(y_train_subset, y_pred)
- metric_results[a_model+'_train_subset_AUPRC_before_ablation'] = auprc_score(y_train_subset, y_pred)
+ metric_results[a_model+'_train_subset_AUPRC_before_ablation'] = average_precision_score(y_train_subset, y_pred)
metric_results[a_model+'_train_subset_F1_before_ablation'] = f1_score(y_train_subset, y_pred > 0.5)
imp_vals = copy.deepcopy(local_fi_score_train_subset)
imp_vals[imp_vals == float("-inf")] = -sys.maxsize - 1
@@ -223,7 +232,7 @@ def compare_estimators(estimators: List[ModelConfig],
else:
ablation_X_train_subset = ablation_to_mean(X_train, X_train_subset, imp_vals, "min", i+1)
ablation_results_auroc_list[i] += roc_auc_score(y_train_subset, ablation_est.predict_proba(ablation_X_train_subset)[:, 1])
- ablation_results_auprc_list[i] += auprc_score(y_train_subset, ablation_est.predict_proba(ablation_X_train_subset)[:, 1])
+ ablation_results_auprc_list[i] += average_precision_score(y_train_subset, ablation_est.predict_proba(ablation_X_train_subset)[:, 1])
ablation_results_f1_list[i] += f1_score(y_train_subset, ablation_est.predict_proba(ablation_X_train_subset)[:, 1] > 0.5)
ablation_results_f1_list = [x / number_of_ablations for x in ablation_results_f1_list]
ablation_results_auroc_list = [x / number_of_ablations for x in ablation_results_auroc_list]
@@ -241,9 +250,9 @@ def compare_estimators(estimators: List[ModelConfig],
for a_model in ablation_models:
ablation_est = ablation_models[a_model]
ablation_est.fit(X_train, y_train)
- y_pred_subset = est.predict_proba(X_test_subset)[:, 1]
+ y_pred_subset = ablation_est.predict_proba(X_test_subset)[:, 1]
metric_results[a_model+'_test_subset_AUROC_before_ablation'] = roc_auc_score(y_test_subset, y_pred_subset)
- metric_results[a_model+'_test_subset_AUPRC_before_ablation'] = auprc_score(y_test_subset, y_pred_subset)
+ metric_results[a_model+'_test_subset_AUPRC_before_ablation'] = average_precision_score(y_test_subset, y_pred_subset)
metric_results[a_model+'_test_subset_F1_before_ablation'] = f1_score(y_test_subset, y_pred_subset > 0.5)
imp_vals = copy.deepcopy(local_fi_score_test_subset)
imp_vals[imp_vals == float("-inf")] = -sys.maxsize - 1
@@ -258,7 +267,7 @@ def compare_estimators(estimators: List[ModelConfig],
else:
ablation_X_test_subset = ablation_to_mean(X_train, X_test_subset, imp_vals, "min", i+1)
ablation_results_auroc_list[i] += roc_auc_score(y_test_subset, ablation_est.predict_proba(ablation_X_test_subset)[:, 1])
- ablation_results_auprc_list[i] += auprc_score(y_test_subset, ablation_est.predict_proba(ablation_X_test_subset)[:, 1])
+ ablation_results_auprc_list[i] += average_precision_score(y_test_subset, ablation_est.predict_proba(ablation_X_test_subset)[:, 1])
ablation_results_f1_list[i] += f1_score(y_test_subset, ablation_est.predict_proba(ablation_X_test_subset)[:, 1] > 0.5)
ablation_results_f1_list = [x / number_of_ablations for x in ablation_results_f1_list]
ablation_results_auroc_list = [x / number_of_ablations for x in ablation_results_auroc_list]
@@ -277,7 +286,7 @@ def compare_estimators(estimators: List[ModelConfig],
ablation_est = ablation_models[a_model]
ablation_est.fit(X_train, y_train)
metric_results[a_model+'_test_subset_AUROC_before_ablation_blank'] = roc_auc_score(y_test_subset, ablation_est.predict(np.zeros(X_test_subset.shape)))
- metric_results[a_model+'_test_subset_AUPRC_before_ablation_blank'] = auprc_score(y_test_subset, ablation_est.predict(np.zeros(X_test_subset.shape)))
+ metric_results[a_model+'_test_subset_AUPRC_before_ablation_blank'] = average_precision_score(y_test_subset, ablation_est.predict(np.zeros(X_test_subset.shape)))
metric_results[a_model+'_test_subset_F1_before_ablation_blank'] = f1_score(y_test_subset, ablation_est.predict(np.zeros(X_test_subset.shape)) > 0.5)
imp_vals = copy.deepcopy(local_fi_score_test_subset)
imp_vals[imp_vals == float("-inf")] = -sys.maxsize - 1
@@ -292,10 +301,11 @@ def compare_estimators(estimators: List[ModelConfig],
else:
ablation_X_test_subset_blank = ablation_by_addition(X_test_subset, imp_vals, "min", i+1)
ablation_results_auroc_list[i] += roc_auc_score(y_test_subset, ablation_est.predict_proba(ablation_X_test_subset_blank)[:, 1])
- ablation_results_auprc_list[i] += auprc_score(y_test_subset, ablation_est.predict_proba(ablation_X_test_subset_blank)[:, 1])
+ ablation_results_auprc_list[i] += average_precision_score(y_test_subset, ablation_est.predict_proba(ablation_X_test_subset_blank)[:, 1])
ablation_results_f1_list[i] += f1_score(y_test_subset, ablation_est.predict_proba(ablation_X_test_subset_blank)[:, 1] > 0.5)
- ablation_results_list = [x / len(seeds) for x in ablation_results_list]
- ablation_results_list_r2 = [x / len(seeds) for x in ablation_results_list_r2]
+ ablation_results_f1_list = [x / number_of_ablations for x in ablation_results_f1_list]
+ ablation_results_auroc_list = [x / number_of_ablations for x in ablation_results_auroc_list]
+ ablation_results_auprc_list = [x / number_of_ablations for x in ablation_results_auprc_list]
for i in range(X_test_subset.shape[1]):
metric_results[f'{a_model}_test_subset_AUROC_after_ablation_{i+1}_blank'] = ablation_results_auroc_list[i]
metric_results[f'{a_model}_test_subset_AUPRC_after_ablation_{i+1}_blank'] = ablation_results_auprc_list[i]
@@ -309,9 +319,9 @@ def compare_estimators(estimators: List[ModelConfig],
for a_model in ablation_models:
ablation_est = ablation_models[a_model]
ablation_est.fit(X_train, y_train)
- y_pred = est.predict_proba(X_test)[:, 1]
+ y_pred = ablation_est.predict_proba(X_test)[:, 1]
metric_results[a_model+'_test_AUROC_before_ablation'] = roc_auc_score(y_test, y_pred)
- metric_results[a_model+'_test_AUPRC_before_ablation'] = auprc_score(y_test, y_pred)
+ metric_results[a_model+'_test_AUPRC_before_ablation'] = average_precision_score(y_test, y_pred)
metric_results[a_model+'_test_F1_before_ablation'] = f1_score(y_test, y_pred > 0.5)
imp_vals = copy.deepcopy(local_fi_score_test)
imp_vals[imp_vals == float("-inf")] = -sys.maxsize - 1
@@ -326,7 +336,7 @@ def compare_estimators(estimators: List[ModelConfig],
else:
ablation_X_test = ablation_to_mean(X_train, X_test, imp_vals, "min", i+1)
ablation_results_auroc_list[i] += roc_auc_score(y_test, ablation_est.predict_proba(ablation_X_test)[:, 1])
- ablation_results_auprc_list[i] += auprc_score(y_test, ablation_est.predict_proba(ablation_X_test)[:, 1])
+ ablation_results_auprc_list[i] += average_precision_score(y_test, ablation_est.predict_proba(ablation_X_test)[:, 1])
ablation_results_f1_list[i] += f1_score(y_test, ablation_est.predict_proba(ablation_X_test)[:, 1] > 0.5)
ablation_results_f1_list = [x / number_of_ablations for x in ablation_results_f1_list]
ablation_results_auroc_list = [x / number_of_ablations for x in ablation_results_auroc_list]
@@ -337,6 +347,16 @@ def compare_estimators(estimators: List[ModelConfig],
metric_results[f'{a_model}_test_F1_after_ablation_{i+1}'] = ablation_results_f1_list[i]
end = time.time()
metric_results['test_data_ablation_time'] = end - start
+ else:
+ for a_model in ablation_models:
+ metric_results[a_model+'_test_AUROC_before_ablation'] = None
+ metric_results[a_model+'_test_AUPRC_before_ablation'] = None
+ metric_results[a_model+'_test_F1_before_ablation'] = None
+ for i in range(X_test.shape[1]):
+ metric_results[f'{a_model}_test_AUROC_after_ablation_{i+1}'] = None
+ metric_results[f'{a_model}_test_AUPRC_after_ablation_{i+1}'] = None
+ metric_results[f'{a_model}_test_F1_after_ablation_{i+1}'] = None
+ metric_results["test_data_ablation_time"] = None
print(f"fi: {fi_est.name} ablation done with time: {end - start}")
# initialize results with metadata and metric results
diff --git a/feature_importance/01_run_ablation_regression.py b/feature_importance/01_run_ablation_regression.py
index 970f233..85e3163 100644
--- a/feature_importance/01_run_ablation_regression.py
+++ b/feature_importance/01_run_ablation_regression.py
@@ -22,7 +22,6 @@
from sklearn.linear_model import LinearRegression
import xgboost as xgb
from imodels.importance import RandomForestPlusRegressor, RandomForestPlusClassifier
-
sys.path.append(".")
sys.path.append("..")
sys.path.append("../..")
@@ -150,6 +149,7 @@ def compare_estimators(estimators: List[ModelConfig],
test_all_mse = mean_squared_error(y_test, est.predict(X_test))
test_all_r2 = r2_score(y_test, est.predict(X_test))
+ np.random.seed(42)
indices_train = np.random.choice(X_train.shape[0], 100, replace=False)
indices_test = np.random.choice(X_test.shape[0], 100, replace=False)
X_train_subset = X_train[indices_train]
@@ -179,15 +179,23 @@ def compare_estimators(estimators: List[ModelConfig],
metric_results[f'ablation_seed_{i}'] = seeds[i]
start = time.time()
local_fi_score_train_subset = fi_est.cls(X_train=X_train, y_train=y_train,
- X_test=X_test, y_test=y_test,
- fit=copy.deepcopy(est), data_fit_on="train", **fi_est.kwargs)
- local_fi_score_test = fi_est.cls(X_train=X_train, y_train=y_train,
- X_test=X_test, y_test=y_test,
- fit=copy.deepcopy(est), data_fit_on="test", **fi_est.kwargs)
- local_fi_score_test_subset = None
+ X_train_subset = X_train_subset, y_train_subset=y_train_subset,
+ X_test=X_test, y_test=y_test,
+ fit=copy.deepcopy(est), data_fit_on="train_subset", **fi_est.kwargs)
+ if fi_est.name not in ["LIME_RF_plus", "Kernel_SHAP_RF_plus"]:
+ local_fi_score_test = fi_est.cls(X_train=X_train, y_train=y_train,
+ X_train_subset = X_train_subset, y_train_subset=y_train_subset,
+ X_test=X_test, y_test=y_test,
+ fit=copy.deepcopy(est), data_fit_on="test", **fi_est.kwargs)
+ else:
+ local_fi_score_test = None
+ local_fi_score_test_subset = fi_est.cls(X_train=X_train, y_train=y_train,
+ X_train_subset = X_train_subset, y_train_subset=y_train_subset,
+ X_test=X_test_subset, y_test=y_test_subset,
+ fit=copy.deepcopy(est), data_fit_on="test", **fi_est.kwargs)
end = time.time()
metric_results['fi_time'] = end - start
- feature_importance_list.append(local_fi_score_train_subset)
+ # feature_importance_list.append(local_fi_score_train_subset)
feature_importance_list.append(local_fi_score_test)
feature_importance_list.append(local_fi_score_test_subset)
@@ -313,6 +321,15 @@ def compare_estimators(estimators: List[ModelConfig],
metric_results[f'{a_model}_test_R_2_after_ablation_{i+1}'] = ablation_results_list_r2[i]
end = time.time()
metric_results['test_data_ablation_time'] = end - start
+ else:
+ for a_model in ablation_models:
+ metric_results[a_model + '_test_MSE_before_ablation'] = None
+ metric_results[a_model + '_test_R_2_before_ablation'] = None
+ for i in range(X_test.shape[1]):
+ metric_results[f'{a_model}_test_MSE_after_ablation_{i+1}'] = None
+ metric_results[f'{a_model}_test_R_2_after_ablation_{i+1}'] = None
+ metric_results["test_data_ablation_time"] = None
+
print(f"fi: {fi_est.name} ablation done with time: {end - start}")
# initialize results with metadata and metric results
diff --git a/feature_importance/diabetes_regression_test.png b/feature_importance/diabetes_regression_test.png
new file mode 100644
index 0000000..5a41e19
Binary files /dev/null and b/feature_importance/diabetes_regression_test.png differ
diff --git a/feature_importance/diabetes_regression_test_subset_1.png b/feature_importance/diabetes_regression_test_subset_1.png
new file mode 100644
index 0000000..1d9b4da
Binary files /dev/null and b/feature_importance/diabetes_regression_test_subset_1.png differ
diff --git a/feature_importance/diabetes_regression_test_subset_2.png b/feature_importance/diabetes_regression_test_subset_2.png
new file mode 100644
index 0000000..03ee891
Binary files /dev/null and b/feature_importance/diabetes_regression_test_subset_2.png differ
diff --git a/feature_importance/diabetes_regression_train.png b/feature_importance/diabetes_regression_train.png
new file mode 100644
index 0000000..cf044fa
Binary files /dev/null and b/feature_importance/diabetes_regression_train.png differ
diff --git a/feature_importance/fi_config/mdi_local/real_data_classification/dgp.py b/feature_importance/fi_config/mdi_local/real_data_classification/dgp.py
index 0e3253c..5833778 100644
--- a/feature_importance/fi_config/mdi_local/real_data_classification/dgp.py
+++ b/feature_importance/fi_config/mdi_local/real_data_classification/dgp.py
@@ -4,30 +4,30 @@
X_DGP = sample_real_data
-X_PARAMS_DICT = {
- "X_fpath": "../data/classification_data/Diabetes/X_diabetes.csv",
- "sample_row_n": None,
- "return_data": "X"
-}
# X_PARAMS_DICT = {
-# "X_fpath": "../data/classification_data/Fico/X_fico.csv",
+# "X_fpath": "../data/classification_data/Diabetes/X_diabetes.csv",
# "sample_row_n": None,
# "return_data": "X"
# }
+X_PARAMS_DICT = {
+ "X_fpath": "../data/classification_data/Fico/X_fico.csv",
+ "sample_row_n": None,
+ "return_data": "X"
+}
# X_PARAMS_DICT = {
# "X_fpath": "../data/classification_data/Juvenile/X_juvenile.csv",
# "sample_row_n": None,
# "return_data": "X"
# }
Y_DGP = sample_real_data
-Y_PARAMS_DICT = {
- "y_fpath": "../data/classification_data/Diabetes/y_diabetes.csv",
- "return_data": "y"
-}
# Y_PARAMS_DICT = {
-# "y_fpath": "../data/classification_data/Fico/y_fico.csv",
+# "y_fpath": "../data/classification_data/Diabetes/y_diabetes.csv",
# "return_data": "y"
# }
+Y_PARAMS_DICT = {
+ "y_fpath": "../data/classification_data/Fico/y_fico.csv",
+ "return_data": "y"
+}
# Y_PARAMS_DICT = {
# "y_fpath": "../data/classification_data/Juvenile/y_juvenile.csv",
# "return_data": "y"
diff --git a/feature_importance/fi_config/mdi_local/real_data_classification/models.py b/feature_importance/fi_config/mdi_local/real_data_classification/models.py
index 7f9d89c..d19fd42 100644
--- a/feature_importance/fi_config/mdi_local/real_data_classification/models.py
+++ b/feature_importance/fi_config/mdi_local/real_data_classification/models.py
@@ -17,9 +17,9 @@
]
FI_ESTIMATORS = [
- [FIModelConfig('LFI_with_raw_RF', LFI_test_evaluation_RF, model_type='tree', splitting_strategy = "train-test")],
- [FIModelConfig('MDI_RF', LFI_test_evaluation_RF, model_type='tree', splitting_strategy = "train-test", other_params={"include_raw": False, "cv_ridge": 0, "calc_loo_coef":False, "sample_split":"inbag"})],
- [FIModelConfig('LFI_with_raw_OOB_RF', LFI_test_evaluation_RF, model_type='tree', splitting_strategy = "train-test", other_params={"sample_split":"oob", "fit_on":"test", "calc_loo_coef":False})],
+ [FIModelConfig('LFI_with_raw_RF', LFI_evaluation_RF, model_type='tree', splitting_strategy = "train-test")],
+ [FIModelConfig('MDI_RF', LFI_evaluation_RF, model_type='tree', splitting_strategy = "train-test", other_params={"include_raw": False, "cv_ridge": 0, "calc_loo_coef":False, "sample_split":"inbag"})],
+ [FIModelConfig('LFI_with_raw_OOB_RF', LFI_evaluation_RF, model_type='tree', splitting_strategy = "train-test", other_params={"sample_split":"oob", "fit_on":"test", "calc_loo_coef":False})],
[FIModelConfig('TreeSHAP_RF', tree_shap_evaluation_RF, model_type='tree', splitting_strategy = "train-test")],
[FIModelConfig('LFI_with_raw_RF_plus', LFI_evaluation_RF_plus, model_type='t_plus', splitting_strategy = "train-test")],
[FIModelConfig('Kernel_SHAP_RF_plus', kernel_shap_evaluation_RF_plus, model_type='t_plus', splitting_strategy = "train-test")],
diff --git a/feature_importance/fi_config/mdi_local/real_data_regression/dgp.py b/feature_importance/fi_config/mdi_local/real_data_regression/dgp.py
index ce133d5..9cdd61d 100644
--- a/feature_importance/fi_config/mdi_local/real_data_regression/dgp.py
+++ b/feature_importance/fi_config/mdi_local/real_data_regression/dgp.py
@@ -9,29 +9,29 @@
# "sample_row_n": None,
# "return_data": "X"
# }
-X_PARAMS_DICT = {
- "X_fpath": "../data/regression_data/Diabetes_regression/X_diabetes_regression.csv",
- "sample_row_n": None,
- "return_data": "X"
-}
# X_PARAMS_DICT = {
-# "X_fpath": "../data/regression_data/Satellite_image/X_satellite_image.csv",
+# "X_fpath": "../data/regression_data/Diabetes_regression/X_diabetes_regression.csv",
# "sample_row_n": None,
# "return_data": "X"
# }
+X_PARAMS_DICT = {
+ "X_fpath": "../data/regression_data/Satellite_image/X_satellite_image.csv",
+ "sample_row_n": None,
+ "return_data": "X"
+}
Y_DGP = sample_real_data
# Y_PARAMS_DICT = {
# "y_fpath": "../data/regression_data/CA_housing/y_california_housing.csv",
# "return_data": "y"
# }
-Y_PARAMS_DICT = {
- "y_fpath": "../data/regression_data/Diabetes_regression/y_diabetes_regression.csv",
- "return_data": "y"
-}
# Y_PARAMS_DICT = {
-# "y_fpath": "../data/regression_data/Satellite_image/y_satellite_image.csv",
+# "y_fpath": "../data/regression_data/Diabetes_regression/y_diabetes_regression.csv",
# "return_data": "y"
# }
+Y_PARAMS_DICT = {
+ "y_fpath": "../data/regression_data/Satellite_image/y_satellite_image.csv",
+ "return_data": "y"
+}
# vary one parameter
VARY_PARAM_NAME = "sample_row_n"
VARY_PARAM_VALS = {"keep_all_rows": None}
\ No newline at end of file
diff --git a/feature_importance/fi_config/mdi_local/real_data_regression/models.py b/feature_importance/fi_config/mdi_local/real_data_regression/models.py
index 3b9d3c9..a209dbf 100644
--- a/feature_importance/fi_config/mdi_local/real_data_regression/models.py
+++ b/feature_importance/fi_config/mdi_local/real_data_regression/models.py
@@ -17,10 +17,10 @@
]
FI_ESTIMATORS = [
- [FIModelConfig('LFI_with_raw_RF', LFI_test_evaluation_RF, model_type='tree', splitting_strategy = "train-test")],
+ [FIModelConfig('LFI_with_raw_RF', LFI_evaluation_RF, model_type='tree', splitting_strategy = "train-test")],
# [FIModelConfig('LFI_with_raw_CV_RF', LFI_test_evaluation_RF, model_type='tree', splitting_strategy = "train-test", other_params={"cv_ridge": 5, "calc_loo_coef":False})],
- [FIModelConfig('MDI_RF', LFI_test_evaluation_RF, model_type='tree', splitting_strategy = "train-test", other_params={"include_raw": False, "cv_ridge": 0, "calc_loo_coef":False, "sample_split":"inbag"})],
- [FIModelConfig('LFI_with_raw_OOB_RF', LFI_test_evaluation_RF, model_type='tree', splitting_strategy = "train-test", other_params={"sample_split":"oob", "fit_on":"test", "calc_loo_coef":False})],
+ [FIModelConfig('MDI_RF', LFI_evaluation_RF, model_type='tree', splitting_strategy = "train-test", other_params={"include_raw": False, "cv_ridge": 0, "calc_loo_coef":False, "sample_split":"inbag"})],
+ [FIModelConfig('LFI_with_raw_OOB_RF', LFI_evaluation_RF, model_type='tree', splitting_strategy = "train-test", other_params={"sample_split":"oob", "fit_on":"test", "calc_loo_coef":False})],
[FIModelConfig('TreeSHAP_RF', tree_shap_evaluation_RF, model_type='tree', splitting_strategy = "train-test")],
[FIModelConfig('LFI_with_raw_RF_plus', LFI_evaluation_RF_plus, model_type='t_plus', splitting_strategy = "train-test")],
[FIModelConfig('Kernel_SHAP_RF_plus', kernel_shap_evaluation_RF_plus, model_type='t_plus', splitting_strategy = "train-test")],
diff --git a/feature_importance/real_data_ablation_visulization_version3.ipynb b/feature_importance/real_data_ablation_visulization_version3.ipynb
index 449bd4f..fb0bac7 100644
--- a/feature_importance/real_data_ablation_visulization_version3.ipynb
+++ b/feature_importance/real_data_ablation_visulization_version3.ipynb
@@ -20,8 +20,8 @@
"outputs": [],
"source": [
"# directory = './results/mdi_local.real_data_regression/diabetes_regression_parallel/varying_sample_row_n/'\n",
- "# directory = './results/mdi_local.real_data_classification/diabetes_classification_parallel/varying_sample_row_n/'\n",
- "directory = './results/mdi_local.real_data_regression/diabetes_regression/varying_sample_row_n'\n",
+ "directory = './results/mdi_local.real_data_regression/diabetes_regression/varying_sample_row_n/'\n",
+ "# directory = './results/mdi_local.real_data_regression/diabetes_regression_new/varying_sample_row_n'\n",
"folder_names = [folder for folder in os.listdir(directory) if os.path.isdir(os.path.join(directory, folder))]\n",
"experiments_seeds = []\n",
"for folder_name in folder_names:\n",
@@ -92,197 +92,475 @@
"
data_split_seed | \n",
" test_all_mse | \n",
" test_all_r2 | \n",
+ " sample_train_0 | \n",
" sample_test_0 | \n",
+ " sample_train_1 | \n",
" sample_test_1 | \n",
+ " sample_train_2 | \n",
" sample_test_2 | \n",
+ " sample_train_3 | \n",
" sample_test_3 | \n",
+ " sample_train_4 | \n",
" sample_test_4 | \n",
+ " sample_train_5 | \n",
" sample_test_5 | \n",
+ " sample_train_6 | \n",
" sample_test_6 | \n",
+ " sample_train_7 | \n",
" sample_test_7 | \n",
+ " sample_train_8 | \n",
" sample_test_8 | \n",
+ " sample_train_9 | \n",
" sample_test_9 | \n",
+ " sample_train_10 | \n",
" sample_test_10 | \n",
+ " sample_train_11 | \n",
" sample_test_11 | \n",
+ " sample_train_12 | \n",
" sample_test_12 | \n",
+ " sample_train_13 | \n",
" sample_test_13 | \n",
+ " sample_train_14 | \n",
" sample_test_14 | \n",
+ " sample_train_15 | \n",
" sample_test_15 | \n",
+ " sample_train_16 | \n",
" sample_test_16 | \n",
+ " sample_train_17 | \n",
" sample_test_17 | \n",
+ " sample_train_18 | \n",
" sample_test_18 | \n",
+ " sample_train_19 | \n",
" sample_test_19 | \n",
+ " sample_train_20 | \n",
" sample_test_20 | \n",
+ " sample_train_21 | \n",
" sample_test_21 | \n",
+ " sample_train_22 | \n",
" sample_test_22 | \n",
+ " sample_train_23 | \n",
" sample_test_23 | \n",
+ " sample_train_24 | \n",
" sample_test_24 | \n",
+ " sample_train_25 | \n",
" sample_test_25 | \n",
+ " sample_train_26 | \n",
" sample_test_26 | \n",
+ " sample_train_27 | \n",
" sample_test_27 | \n",
+ " sample_train_28 | \n",
" sample_test_28 | \n",
+ " sample_train_29 | \n",
" sample_test_29 | \n",
+ " sample_train_30 | \n",
" sample_test_30 | \n",
+ " sample_train_31 | \n",
" sample_test_31 | \n",
+ " sample_train_32 | \n",
" sample_test_32 | \n",
+ " sample_train_33 | \n",
" sample_test_33 | \n",
+ " sample_train_34 | \n",
" sample_test_34 | \n",
+ " sample_train_35 | \n",
" sample_test_35 | \n",
+ " sample_train_36 | \n",
" sample_test_36 | \n",
+ " sample_train_37 | \n",
" sample_test_37 | \n",
+ " sample_train_38 | \n",
" sample_test_38 | \n",
+ " sample_train_39 | \n",
" sample_test_39 | \n",
+ " sample_train_40 | \n",
" sample_test_40 | \n",
+ " sample_train_41 | \n",
" sample_test_41 | \n",
+ " sample_train_42 | \n",
" sample_test_42 | \n",
+ " sample_train_43 | \n",
" sample_test_43 | \n",
+ " sample_train_44 | \n",
" sample_test_44 | \n",
+ " sample_train_45 | \n",
" sample_test_45 | \n",
+ " sample_train_46 | \n",
" sample_test_46 | \n",
+ " sample_train_47 | \n",
" sample_test_47 | \n",
+ " sample_train_48 | \n",
" sample_test_48 | \n",
+ " sample_train_49 | \n",
" sample_test_49 | \n",
+ " sample_train_50 | \n",
" sample_test_50 | \n",
+ " sample_train_51 | \n",
" sample_test_51 | \n",
+ " sample_train_52 | \n",
" sample_test_52 | \n",
+ " sample_train_53 | \n",
" sample_test_53 | \n",
+ " sample_train_54 | \n",
" sample_test_54 | \n",
+ " sample_train_55 | \n",
" sample_test_55 | \n",
+ " sample_train_56 | \n",
" sample_test_56 | \n",
+ " sample_train_57 | \n",
" sample_test_57 | \n",
+ " sample_train_58 | \n",
" sample_test_58 | \n",
+ " sample_train_59 | \n",
" sample_test_59 | \n",
+ " sample_train_60 | \n",
" sample_test_60 | \n",
+ " sample_train_61 | \n",
" sample_test_61 | \n",
+ " sample_train_62 | \n",
" sample_test_62 | \n",
+ " sample_train_63 | \n",
" sample_test_63 | \n",
+ " sample_train_64 | \n",
" sample_test_64 | \n",
+ " sample_train_65 | \n",
" sample_test_65 | \n",
+ " sample_train_66 | \n",
" sample_test_66 | \n",
+ " sample_train_67 | \n",
" sample_test_67 | \n",
+ " sample_train_68 | \n",
" sample_test_68 | \n",
+ " sample_train_69 | \n",
" sample_test_69 | \n",
+ " sample_train_70 | \n",
" sample_test_70 | \n",
+ " sample_train_71 | \n",
" sample_test_71 | \n",
+ " sample_train_72 | \n",
" sample_test_72 | \n",
+ " sample_train_73 | \n",
" sample_test_73 | \n",
+ " sample_train_74 | \n",
" sample_test_74 | \n",
+ " sample_train_75 | \n",
" sample_test_75 | \n",
+ " sample_train_76 | \n",
" sample_test_76 | \n",
+ " sample_train_77 | \n",
" sample_test_77 | \n",
+ " sample_train_78 | \n",
" sample_test_78 | \n",
+ " sample_train_79 | \n",
" sample_test_79 | \n",
+ " sample_train_80 | \n",
" sample_test_80 | \n",
+ " sample_train_81 | \n",
" sample_test_81 | \n",
+ " sample_train_82 | \n",
" sample_test_82 | \n",
+ " sample_train_83 | \n",
" sample_test_83 | \n",
+ " sample_train_84 | \n",
" sample_test_84 | \n",
+ " sample_train_85 | \n",
" sample_test_85 | \n",
+ " sample_train_86 | \n",
" sample_test_86 | \n",
+ " sample_train_87 | \n",
" sample_test_87 | \n",
+ " sample_train_88 | \n",
" sample_test_88 | \n",
+ " sample_train_89 | \n",
" sample_test_89 | \n",
+ " sample_train_90 | \n",
" sample_test_90 | \n",
+ " sample_train_91 | \n",
" sample_test_91 | \n",
+ " sample_train_92 | \n",
" sample_test_92 | \n",
+ " sample_train_93 | \n",
" sample_test_93 | \n",
+ " sample_train_94 | \n",
" sample_test_94 | \n",
+ " sample_train_95 | \n",
" sample_test_95 | \n",
+ " sample_train_96 | \n",
" sample_test_96 | \n",
+ " sample_train_97 | \n",
" sample_test_97 | \n",
+ " sample_train_98 | \n",
" sample_test_98 | \n",
+ " sample_train_99 | \n",
" sample_test_99 | \n",
" ablation_seed_0 | \n",
" fi_time | \n",
- " RF_Regressor_train_MSE_before_ablation | \n",
- " RF_Regressor_train_R_2_before_ablation | \n",
- " RF_Regressor_train_MSE_after_ablation_1 | \n",
- " RF_Regressor_train_R_2_after_ablation_1 | \n",
- " RF_Regressor_train_MSE_after_ablation_2 | \n",
- " RF_Regressor_train_R_2_after_ablation_2 | \n",
- " RF_Regressor_train_MSE_after_ablation_3 | \n",
- " RF_Regressor_train_R_2_after_ablation_3 | \n",
- " RF_Regressor_train_MSE_after_ablation_4 | \n",
- " RF_Regressor_train_R_2_after_ablation_4 | \n",
- " RF_Regressor_train_MSE_after_ablation_5 | \n",
- " RF_Regressor_train_R_2_after_ablation_5 | \n",
- " RF_Regressor_train_MSE_after_ablation_6 | \n",
- " RF_Regressor_train_R_2_after_ablation_6 | \n",
- " RF_Regressor_train_MSE_after_ablation_7 | \n",
- " RF_Regressor_train_R_2_after_ablation_7 | \n",
- " RF_Regressor_train_MSE_after_ablation_8 | \n",
- " RF_Regressor_train_R_2_after_ablation_8 | \n",
- " RF_Regressor_train_MSE_after_ablation_9 | \n",
- " RF_Regressor_train_R_2_after_ablation_9 | \n",
- " RF_Regressor_train_MSE_after_ablation_10 | \n",
- " RF_Regressor_train_R_2_after_ablation_10 | \n",
- " Linear_train_MSE_before_ablation | \n",
- " Linear_train_R_2_before_ablation | \n",
- " Linear_train_MSE_after_ablation_1 | \n",
- " Linear_train_R_2_after_ablation_1 | \n",
- " Linear_train_MSE_after_ablation_2 | \n",
- " Linear_train_R_2_after_ablation_2 | \n",
- " Linear_train_MSE_after_ablation_3 | \n",
- " Linear_train_R_2_after_ablation_3 | \n",
- " Linear_train_MSE_after_ablation_4 | \n",
- " Linear_train_R_2_after_ablation_4 | \n",
- " Linear_train_MSE_after_ablation_5 | \n",
- " Linear_train_R_2_after_ablation_5 | \n",
- " Linear_train_MSE_after_ablation_6 | \n",
- " Linear_train_R_2_after_ablation_6 | \n",
- " Linear_train_MSE_after_ablation_7 | \n",
- " Linear_train_R_2_after_ablation_7 | \n",
- " Linear_train_MSE_after_ablation_8 | \n",
- " Linear_train_R_2_after_ablation_8 | \n",
- " Linear_train_MSE_after_ablation_9 | \n",
- " Linear_train_R_2_after_ablation_9 | \n",
- " Linear_train_MSE_after_ablation_10 | \n",
- " Linear_train_R_2_after_ablation_10 | \n",
- " XGB_Regressor_train_MSE_before_ablation | \n",
- " XGB_Regressor_train_R_2_before_ablation | \n",
- " XGB_Regressor_train_MSE_after_ablation_1 | \n",
- " XGB_Regressor_train_R_2_after_ablation_1 | \n",
- " XGB_Regressor_train_MSE_after_ablation_2 | \n",
- " XGB_Regressor_train_R_2_after_ablation_2 | \n",
- " XGB_Regressor_train_MSE_after_ablation_3 | \n",
- " XGB_Regressor_train_R_2_after_ablation_3 | \n",
- " XGB_Regressor_train_MSE_after_ablation_4 | \n",
- " XGB_Regressor_train_R_2_after_ablation_4 | \n",
- " XGB_Regressor_train_MSE_after_ablation_5 | \n",
- " XGB_Regressor_train_R_2_after_ablation_5 | \n",
- " XGB_Regressor_train_MSE_after_ablation_6 | \n",
- " XGB_Regressor_train_R_2_after_ablation_6 | \n",
- " XGB_Regressor_train_MSE_after_ablation_7 | \n",
- " XGB_Regressor_train_R_2_after_ablation_7 | \n",
- " XGB_Regressor_train_MSE_after_ablation_8 | \n",
- " XGB_Regressor_train_R_2_after_ablation_8 | \n",
- " XGB_Regressor_train_MSE_after_ablation_9 | \n",
- " XGB_Regressor_train_R_2_after_ablation_9 | \n",
- " XGB_Regressor_train_MSE_after_ablation_10 | \n",
- " XGB_Regressor_train_R_2_after_ablation_10 | \n",
- " RF_Plus_Regressor_train_MSE_before_ablation | \n",
- " RF_Plus_Regressor_train_R_2_before_ablation | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_1 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_1 | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_2 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_2 | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_3 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_3 | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_4 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_4 | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_5 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_5 | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_6 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_6 | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_7 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_7 | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_8 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_8 | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_9 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_9 | \n",
- " RF_Plus_Regressor_train_MSE_after_ablation_10 | \n",
- " RF_Plus_Regressor_train_R_2_after_ablation_10 | \n",
- " train_data_ablation_time | \n",
+ " RF_Regressor_train_subset_MSE_before_ablation | \n",
+ " RF_Regressor_train_subset_R_2_before_ablation | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_1 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_1 | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_2 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_2 | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_3 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_3 | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_4 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_4 | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_5 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_5 | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_6 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_6 | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_7 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_7 | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_8 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_8 | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_9 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_9 | \n",
+ " RF_Regressor_train_subset_MSE_after_ablation_10 | \n",
+ " RF_Regressor_train_subset_R_2_after_ablation_10 | \n",
+ " Linear_train_subset_MSE_before_ablation | \n",
+ " Linear_train_subset_R_2_before_ablation | \n",
+ " Linear_train_subset_MSE_after_ablation_1 | \n",
+ " Linear_train_subset_R_2_after_ablation_1 | \n",
+ " Linear_train_subset_MSE_after_ablation_2 | \n",
+ " Linear_train_subset_R_2_after_ablation_2 | \n",
+ " Linear_train_subset_MSE_after_ablation_3 | \n",
+ " Linear_train_subset_R_2_after_ablation_3 | \n",
+ " Linear_train_subset_MSE_after_ablation_4 | \n",
+ " Linear_train_subset_R_2_after_ablation_4 | \n",
+ " Linear_train_subset_MSE_after_ablation_5 | \n",
+ " Linear_train_subset_R_2_after_ablation_5 | \n",
+ " Linear_train_subset_MSE_after_ablation_6 | \n",
+ " Linear_train_subset_R_2_after_ablation_6 | \n",
+ " Linear_train_subset_MSE_after_ablation_7 | \n",
+ " Linear_train_subset_R_2_after_ablation_7 | \n",
+ " Linear_train_subset_MSE_after_ablation_8 | \n",
+ " Linear_train_subset_R_2_after_ablation_8 | \n",
+ " Linear_train_subset_MSE_after_ablation_9 | \n",
+ " Linear_train_subset_R_2_after_ablation_9 | \n",
+ " Linear_train_subset_MSE_after_ablation_10 | \n",
+ " Linear_train_subset_R_2_after_ablation_10 | \n",
+ " XGB_Regressor_train_subset_MSE_before_ablation | \n",
+ " XGB_Regressor_train_subset_R_2_before_ablation | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_1 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_1 | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_2 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_2 | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_3 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_3 | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_4 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_4 | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_5 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_5 | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_6 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_6 | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_7 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_7 | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_8 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_8 | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_9 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_9 | \n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_10 | \n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_10 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_before_ablation | \n",
+ " RF_Plus_Regressor_train_subset_R_2_before_ablation | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_1 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_1 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_2 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_2 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_3 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_3 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_4 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_4 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_5 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_5 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_6 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_6 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_7 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_7 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_8 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_8 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_9 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_9 | \n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_10 | \n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_10 | \n",
+ " train_subset_ablation_time | \n",
+ " RF_Regressor_test_subset_MSE_before_ablation | \n",
+ " RF_Regressor_test_subset_R_2_before_ablation | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_1 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_1 | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_2 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_2 | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_3 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_3 | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_4 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_4 | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_5 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_5 | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_6 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_6 | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_7 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_7 | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_8 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_8 | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_9 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_9 | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_10 | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_10 | \n",
+ " Linear_test_subset_MSE_before_ablation | \n",
+ " Linear_test_subset_R_2_before_ablation | \n",
+ " Linear_test_subset_MSE_after_ablation_1 | \n",
+ " Linear_test_subset_R_2_after_ablation_1 | \n",
+ " Linear_test_subset_MSE_after_ablation_2 | \n",
+ " Linear_test_subset_R_2_after_ablation_2 | \n",
+ " Linear_test_subset_MSE_after_ablation_3 | \n",
+ " Linear_test_subset_R_2_after_ablation_3 | \n",
+ " Linear_test_subset_MSE_after_ablation_4 | \n",
+ " Linear_test_subset_R_2_after_ablation_4 | \n",
+ " Linear_test_subset_MSE_after_ablation_5 | \n",
+ " Linear_test_subset_R_2_after_ablation_5 | \n",
+ " Linear_test_subset_MSE_after_ablation_6 | \n",
+ " Linear_test_subset_R_2_after_ablation_6 | \n",
+ " Linear_test_subset_MSE_after_ablation_7 | \n",
+ " Linear_test_subset_R_2_after_ablation_7 | \n",
+ " Linear_test_subset_MSE_after_ablation_8 | \n",
+ " Linear_test_subset_R_2_after_ablation_8 | \n",
+ " Linear_test_subset_MSE_after_ablation_9 | \n",
+ " Linear_test_subset_R_2_after_ablation_9 | \n",
+ " Linear_test_subset_MSE_after_ablation_10 | \n",
+ " Linear_test_subset_R_2_after_ablation_10 | \n",
+ " XGB_Regressor_test_subset_MSE_before_ablation | \n",
+ " XGB_Regressor_test_subset_R_2_before_ablation | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_1 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_1 | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_2 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_2 | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_3 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_3 | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_4 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_4 | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_5 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_5 | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_6 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_6 | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_7 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_7 | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_8 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_8 | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_9 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_9 | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_10 | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_10 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_before_ablation | \n",
+ " RF_Plus_Regressor_test_subset_R_2_before_ablation | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_1 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_1 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_2 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_2 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_3 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_3 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_4 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_4 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_5 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_5 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_6 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_6 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_7 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_7 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_8 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_8 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_9 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_9 | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_10 | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_10 | \n",
+ " test_subset_ablation_time | \n",
+ " RF_Regressor_test_subset_MSE_before_ablation_blank | \n",
+ " RF_Regressor_test_subset_R_2_before_ablation_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_1_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_1_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_2_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_2_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_3_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_3_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_4_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_4_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_5_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_5_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_6_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_6_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_7_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_7_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_8_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_8_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_9_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_9_blank | \n",
+ " RF_Regressor_test_subset_MSE_after_ablation_10_blank | \n",
+ " RF_Regressor_test_subset_R_2_after_ablation_10_blank | \n",
+ " Linear_test_subset_MSE_before_ablation_blank | \n",
+ " Linear_test_subset_R_2_before_ablation_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_1_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_1_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_2_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_2_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_3_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_3_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_4_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_4_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_5_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_5_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_6_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_6_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_7_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_7_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_8_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_8_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_9_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_9_blank | \n",
+ " Linear_test_subset_MSE_after_ablation_10_blank | \n",
+ " Linear_test_subset_R_2_after_ablation_10_blank | \n",
+ " XGB_Regressor_test_subset_MSE_before_ablation_blank | \n",
+ " XGB_Regressor_test_subset_R_2_before_ablation_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_1_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_1_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_2_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_2_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_3_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_3_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_4_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_4_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_5_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_5_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_6_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_6_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_7_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_7_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_8_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_8_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_9_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_9_blank | \n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_10_blank | \n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_10_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_before_ablation_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_before_ablation_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_1_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_1_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_2_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_2_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_3_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_3_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_4_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_4_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_5_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_5_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_6_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_6_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_7_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_7_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_8_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_8_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_9_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_9_blank | \n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_10_blank | \n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_10_blank | \n",
+ " test_subset_blank_ablation_time | \n",
" RF_Regressor_test_MSE_before_ablation | \n",
" RF_Regressor_test_R_2_before_ablation | \n",
" RF_Regressor_test_MSE_after_ablation_1 | \n",
@@ -396,294 +674,1738 @@
" 296 | \n",
" 146 | \n",
" 10 | \n",
+ " 9 | \n",
+ " 2640.499813 | \n",
+ " 0.535380 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
" 4 | \n",
- " 3167.314235 | \n",
- " 0.445492 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
+ " 6 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 545 | \n",
+ " 8.739464 | \n",
+ " 1437.058926 | \n",
+ " 0.740320 | \n",
+ " 2450.453723 | \n",
+ " 0.557198 | \n",
+ " 3708.135984 | \n",
+ " 0.329932 | \n",
+ " 4626.637491 | \n",
+ " 0.163956 | \n",
+ " 4988.459417 | \n",
+ " 0.098574 | \n",
+ " 5232.901749 | \n",
+ " 0.054403 | \n",
+ " 5437.430361 | \n",
+ " 0.017444 | \n",
+ " 5421.293849 | \n",
+ " 0.020360 | \n",
+ " 5443.743634 | \n",
+ " 0.016303 | \n",
+ " 5494.702450 | \n",
+ " 0.007095 | \n",
+ " 5539.523521 | \n",
+ " -0.001004 | \n",
+ " 2751.227274 | \n",
+ " 0.502847 | \n",
+ " 4010.135272 | \n",
+ " 0.275360 | \n",
+ " 5532.061236 | \n",
+ " 0.000344 | \n",
+ " 6235.149787 | \n",
+ " -0.126705 | \n",
+ " 6665.951971 | \n",
+ " -0.204552 | \n",
+ " 6788.027586 | \n",
+ " -0.226612 | \n",
+ " 7155.239308 | \n",
+ " -0.292968 | \n",
+ " 6938.669534 | \n",
+ " -0.253833 | \n",
+ " 6945.021356 | \n",
+ " -0.254981 | \n",
+ " 6428.621982 | \n",
+ " -0.161666 | \n",
+ " 5537.963738 | \n",
+ " -0.000722 | \n",
+ " 0.018187 | \n",
+ " 0.999997 | \n",
+ " 1625.010655 | \n",
+ " 0.706357 | \n",
+ " 3727.227862 | \n",
+ " 0.326482 | \n",
+ " 4758.802828 | \n",
+ " 0.140074 | \n",
+ " 5438.045521 | \n",
+ " 0.017333 | \n",
+ " 6086.223432 | \n",
+ " -0.099794 | \n",
+ " 6003.810755 | \n",
+ " -0.084902 | \n",
+ " 5914.676886 | \n",
+ " -0.068795 | \n",
+ " 5957.839900 | \n",
+ " -0.076595 | \n",
+ " 6074.783783 | \n",
+ " -0.097727 | \n",
+ " 6105.231363 | \n",
+ " -0.103229 | \n",
+ " 2144.267875 | \n",
+ " 0.612526 | \n",
+ " 3060.549288 | \n",
+ " 0.446952 | \n",
+ " 4420.021303 | \n",
+ " 0.201292 | \n",
+ " 5162.192629 | \n",
+ " 0.067180 | \n",
+ " 5474.959682 | \n",
+ " 0.010663 | \n",
+ " 5641.270595 | \n",
+ " -0.019390 | \n",
+ " 5661.113577 | \n",
+ " -0.022976 | \n",
+ " 5588.716961 | \n",
+ " -0.009894 | \n",
+ " 5570.355417 | \n",
+ " -0.006576 | \n",
+ " 5583.728055 | \n",
+ " -0.008992 | \n",
+ " 5566.322332 | \n",
+ " -0.005847 | \n",
+ " 8.492494 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 3558.027039 | \n",
+ " 0.392540 | \n",
+ " 4541.111469 | \n",
+ " 0.224698 | \n",
+ " 5108.780808 | \n",
+ " 0.127781 | \n",
+ " 5549.938512 | \n",
+ " 0.052462 | \n",
+ " 5575.079768 | \n",
+ " 0.048170 | \n",
+ " 5670.569231 | \n",
+ " 0.031867 | \n",
+ " 5714.830950 | \n",
+ " 0.024310 | \n",
+ " 5776.424753 | \n",
+ " 0.013794 | \n",
+ " 5872.761365 | \n",
+ " -0.002653 | \n",
+ " 5889.339711 | \n",
+ " -0.005484 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 4121.029876 | \n",
+ " 0.296419 | \n",
+ " 5581.975377 | \n",
+ " 0.046992 | \n",
+ " 6449.756912 | \n",
+ " -0.101164 | \n",
+ " 6842.982437 | \n",
+ " -0.168299 | \n",
+ " 7065.868591 | \n",
+ " -0.206352 | \n",
+ " 7600.334465 | \n",
+ " -0.297601 | \n",
+ " 7801.583405 | \n",
+ " -0.331960 | \n",
+ " 7891.538915 | \n",
+ " -0.347318 | \n",
+ " 6808.265390 | \n",
+ " -0.162372 | \n",
+ " 5858.937117 | \n",
+ " -0.000293 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 3667.804311 | \n",
+ " 0.373798 | \n",
+ " 5488.665183 | \n",
+ " 0.062923 | \n",
+ " 5822.513161 | \n",
+ " 0.005925 | \n",
+ " 6037.023411 | \n",
+ " -0.030698 | \n",
+ " 5949.756252 | \n",
+ " -0.015799 | \n",
+ " 6223.517883 | \n",
+ " -0.062538 | \n",
+ " 6210.989156 | \n",
+ " -0.060399 | \n",
+ " 6244.319537 | \n",
+ " -0.066089 | \n",
+ " 6324.119549 | \n",
+ " -0.079714 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 3573.380509 | \n",
+ " 0.389919 | \n",
+ " 4710.979622 | \n",
+ " 0.195697 | \n",
+ " 5465.488800 | \n",
+ " 0.066880 | \n",
+ " 5856.644776 | \n",
+ " 0.000098 | \n",
+ " 5847.537802 | \n",
+ " 0.001653 | \n",
+ " 5890.341430 | \n",
+ " -0.005655 | \n",
+ " 5891.401596 | \n",
+ " -0.005836 | \n",
+ " 5870.056142 | \n",
+ " -0.002192 | \n",
+ " 5882.308542 | \n",
+ " -0.004283 | \n",
+ " 5862.875775 | \n",
+ " -0.000966 | \n",
+ " 8.213507 | \n",
+ " 5880.887238 | \n",
+ " -0.004041 | \n",
+ " 3912.099558 | \n",
+ " 0.332089 | \n",
+ " 3260.557037 | \n",
+ " 0.443327 | \n",
+ " 2963.289802 | \n",
+ " 0.494079 | \n",
+ " 2835.532455 | \n",
+ " 0.515891 | \n",
+ " 2839.168591 | \n",
+ " 0.515270 | \n",
+ " 2809.721585 | \n",
+ " 0.520298 | \n",
+ " 2729.778409 | \n",
+ " 0.533946 | \n",
+ " 2692.894402 | \n",
+ " 0.540244 | \n",
+ " 2680.209497 | \n",
+ " 0.542409 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 5857.395491 | \n",
+ " -0.000030 | \n",
+ " 3434.906829 | \n",
+ " 0.413560 | \n",
+ " 2906.874850 | \n",
+ " 0.503711 | \n",
+ " 2776.668307 | \n",
+ " 0.525941 | \n",
+ " 3004.535201 | \n",
+ " 0.487037 | \n",
+ " 3040.159140 | \n",
+ " 0.480955 | \n",
+ " 3226.471955 | \n",
+ " 0.449146 | \n",
+ " 3279.136428 | \n",
+ " 0.440155 | \n",
+ " 3209.250097 | \n",
+ " 0.452086 | \n",
+ " 2989.483161 | \n",
+ " 0.489607 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 4078.941418 | \n",
+ " 0.303604 | \n",
+ " 4141.802429 | \n",
+ " 0.292872 | \n",
+ " 4171.239813 | \n",
+ " 0.287846 | \n",
+ " 4144.247041 | \n",
+ " 0.292455 | \n",
+ " 4009.638211 | \n",
+ " 0.315437 | \n",
+ " 3955.399010 | \n",
+ " 0.324697 | \n",
+ " 3978.358871 | \n",
+ " 0.320777 | \n",
+ " 3902.886409 | \n",
+ " 0.333662 | \n",
+ " 3661.068636 | \n",
+ " 0.374948 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 5862.016707 | \n",
+ " -0.000819 | \n",
+ " 3776.067195 | \n",
+ " 0.355314 | \n",
+ " 3002.695954 | \n",
+ " 0.487351 | \n",
+ " 2704.167022 | \n",
+ " 0.538319 | \n",
+ " 2643.172114 | \n",
+ " 0.548733 | \n",
+ " 2667.464939 | \n",
+ " 0.544585 | \n",
+ " 2642.388141 | \n",
+ " 0.548866 | \n",
+ " 2565.443158 | \n",
+ " 0.562003 | \n",
+ " 2541.553235 | \n",
+ " 0.566082 | \n",
+ " 2544.841992 | \n",
+ " 0.565520 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 8.630264 | \n",
+ " 2640.499813 | \n",
+ " 0.535380 | \n",
+ " 3524.835070 | \n",
+ " 0.379773 | \n",
+ " 4339.761162 | \n",
+ " 0.236380 | \n",
+ " 5044.129946 | \n",
+ " 0.112440 | \n",
+ " 5423.189116 | \n",
+ " 0.045741 | \n",
+ " 5559.160140 | \n",
+ " 0.021816 | \n",
+ " 5558.547528 | \n",
+ " 0.021923 | \n",
+ " 5620.116672 | \n",
+ " 0.011090 | \n",
+ " 5710.918759 | \n",
+ " -0.004888 | \n",
+ " 5776.883880 | \n",
+ " -0.016495 | \n",
+ " 5801.671997 | \n",
+ " -0.020857 | \n",
+ " 2496.785106 | \n",
+ " 0.560668 | \n",
+ " 3933.440887 | \n",
+ " 0.307876 | \n",
+ " 5378.186635 | \n",
+ " 0.053660 | \n",
+ " 6372.090383 | \n",
+ " -0.121227 | \n",
+ " 6771.155629 | \n",
+ " -0.191446 | \n",
+ " 7068.389560 | \n",
+ " -0.243747 | \n",
+ " 7447.880628 | \n",
+ " -0.310522 | \n",
+ " 7634.217290 | \n",
+ " -0.343309 | \n",
+ " 7542.656034 | \n",
+ " -0.327198 | \n",
+ " 6778.699347 | \n",
+ " -0.192773 | \n",
+ " 5725.785543 | \n",
+ " -0.007504 | \n",
+ " 3494.999877 | \n",
+ " 0.385023 | \n",
+ " 4013.099838 | \n",
+ " 0.293859 | \n",
+ " 5025.053741 | \n",
+ " 0.115796 | \n",
+ " 5501.079765 | \n",
+ " 0.032035 | \n",
+ " 5797.321121 | \n",
+ " -0.020091 | \n",
+ " 5843.247374 | \n",
+ " -0.028172 | \n",
+ " 5892.623117 | \n",
+ " -0.036860 | \n",
+ " 5822.535066 | \n",
+ " -0.024528 | \n",
+ " 5913.358559 | \n",
+ " -0.040509 | \n",
+ " 5945.208529 | \n",
+ " -0.046113 | \n",
+ " 5919.422152 | \n",
+ " -0.041576 | \n",
+ " 2466.857536 | \n",
+ " 0.565934 | \n",
+ " 3486.670871 | \n",
+ " 0.386489 | \n",
+ " 4501.848106 | \n",
+ " 0.207859 | \n",
+ " 5291.148962 | \n",
+ " 0.068975 | \n",
+ " 5664.603936 | \n",
+ " 0.003262 | \n",
+ " 5755.469084 | \n",
+ " -0.012727 | \n",
+ " 5712.231598 | \n",
+ " -0.005119 | \n",
+ " 5715.404233 | \n",
+ " -0.005677 | \n",
+ " 5698.990643 | \n",
+ " -0.002789 | \n",
+ " 5717.216380 | \n",
+ " -0.005996 | \n",
+ " 5691.215026 | \n",
+ " -0.001421 | \n",
+ " 8.682843 | \n",
+ " 9 | \n",
" NaN | \n",
+ " \n",
+ " \n",
+ " 1 | \n",
" NaN | \n",
+ " keep_all_rows | \n",
+ " 0 | \n",
+ " 100.0 | \n",
+ " 5.0 | \n",
+ " 0.33 | \n",
+ " 42.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
+ " RF | \n",
+ " LFI_with_raw_RF | \n",
+ " 296 | \n",
+ " 146 | \n",
+ " 10 | \n",
+ " 9 | \n",
+ " 2640.499813 | \n",
+ " 0.535380 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
+ " 4 | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
+ " 6 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 545 | \n",
+ " 9.849160 | \n",
+ " 1437.058926 | \n",
+ " 0.740320 | \n",
+ " 2554.479820 | \n",
+ " 0.538400 | \n",
+ " 3776.859055 | \n",
+ " 0.317513 | \n",
+ " 4555.990329 | \n",
+ " 0.176722 | \n",
+ " 5094.477192 | \n",
+ " 0.079417 | \n",
+ " 5291.593590 | \n",
+ " 0.043797 | \n",
+ " 5426.338268 | \n",
+ " 0.019449 | \n",
+ " 5451.723835 | \n",
+ " 0.014861 | \n",
+ " 5477.274281 | \n",
+ " 0.010244 | \n",
+ " 5514.501633 | \n",
+ " 0.003517 | \n",
+ " 5539.523521 | \n",
+ " -0.001004 | \n",
+ " 2751.227274 | \n",
+ " 0.502847 | \n",
+ " 4077.155488 | \n",
+ " 0.263249 | \n",
+ " 5679.643882 | \n",
+ " -0.026324 | \n",
+ " 6227.670680 | \n",
+ " -0.125354 | \n",
+ " 6600.313727 | \n",
+ " -0.192691 | \n",
+ " 6851.937171 | \n",
+ " -0.238160 | \n",
+ " 6859.504452 | \n",
+ " -0.239528 | \n",
+ " 6402.080061 | \n",
+ " -0.156870 | \n",
+ " 6190.738584 | \n",
+ " -0.118680 | \n",
+ " 6055.316091 | \n",
+ " -0.094209 | \n",
+ " 5537.963738 | \n",
+ " -0.000722 | \n",
+ " 0.018187 | \n",
+ " 0.999997 | \n",
+ " 1811.187362 | \n",
+ " 0.672714 | \n",
+ " 3768.911516 | \n",
+ " 0.318949 | \n",
+ " 4799.059708 | \n",
+ " 0.132799 | \n",
+ " 5389.715225 | \n",
+ " 0.026066 | \n",
+ " 5710.096369 | \n",
+ " -0.031827 | \n",
+ " 5721.904769 | \n",
+ " -0.033961 | \n",
+ " 5982.301528 | \n",
+ " -0.081015 | \n",
+ " 6049.655530 | \n",
+ " -0.093186 | \n",
+ " 6140.066210 | \n",
+ " -0.109524 | \n",
+ " 6105.231363 | \n",
+ " -0.103229 | \n",
+ " 2144.267875 | \n",
+ " 0.612526 | \n",
+ " 3176.445261 | \n",
+ " 0.426009 | \n",
+ " 4460.833780 | \n",
+ " 0.193917 | \n",
+ " 5097.059761 | \n",
+ " 0.078950 | \n",
+ " 5485.856853 | \n",
+ " 0.008693 | \n",
+ " 5608.567209 | \n",
+ " -0.013481 | \n",
+ " 5606.850647 | \n",
+ " -0.013170 | \n",
+ " 5631.777151 | \n",
+ " -0.017675 | \n",
+ " 5627.949257 | \n",
+ " -0.016983 | \n",
+ " 5616.876738 | \n",
+ " -0.014982 | \n",
+ " 5566.322332 | \n",
+ " -0.005847 | \n",
+ " 8.477902 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 3580.553278 | \n",
+ " 0.388694 | \n",
+ " 4515.904516 | \n",
+ " 0.229002 | \n",
+ " 5136.563348 | \n",
+ " 0.123037 | \n",
+ " 5524.671544 | \n",
+ " 0.056776 | \n",
+ " 5632.072864 | \n",
+ " 0.038439 | \n",
+ " 5732.292023 | \n",
+ " 0.021329 | \n",
+ " 5748.309155 | \n",
+ " 0.018594 | \n",
+ " 5834.804713 | \n",
+ " 0.003827 | \n",
+ " 5893.413600 | \n",
+ " -0.006179 | \n",
+ " 5889.339711 | \n",
+ " -0.005484 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 4124.763026 | \n",
+ " 0.295781 | \n",
+ " 5536.778873 | \n",
+ " 0.054709 | \n",
+ " 6523.833742 | \n",
+ " -0.113811 | \n",
+ " 7003.490348 | \n",
+ " -0.195702 | \n",
+ " 7133.726667 | \n",
+ " -0.217937 | \n",
+ " 7427.707370 | \n",
+ " -0.268129 | \n",
+ " 7647.662285 | \n",
+ " -0.305681 | \n",
+ " 6644.842594 | \n",
+ " -0.134470 | \n",
+ " 6017.978299 | \n",
+ " -0.027446 | \n",
+ " 5858.937117 | \n",
+ " -0.000293 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 3683.765603 | \n",
+ " 0.371073 | \n",
+ " 5290.726366 | \n",
+ " 0.096717 | \n",
+ " 5859.991940 | \n",
+ " -0.000473 | \n",
+ " 5977.632024 | \n",
+ " -0.020558 | \n",
+ " 5873.903853 | \n",
+ " -0.002848 | \n",
+ " 6192.089129 | \n",
+ " -0.057172 | \n",
+ " 6217.811390 | \n",
+ " -0.061564 | \n",
+ " 6247.683148 | \n",
+ " -0.066664 | \n",
+ " 6292.015930 | \n",
+ " -0.074233 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 3598.856442 | \n",
+ " 0.385569 | \n",
+ " 4652.267727 | \n",
+ " 0.205721 | \n",
+ " 5453.579322 | \n",
+ " 0.068913 | \n",
+ " 5852.723797 | \n",
+ " 0.000768 | \n",
+ " 5860.980468 | \n",
+ " -0.000642 | \n",
+ " 5901.633728 | \n",
+ " -0.007583 | \n",
+ " 5867.400592 | \n",
+ " -0.001738 | \n",
+ " 5842.365202 | \n",
+ " 0.002536 | \n",
+ " 5865.341473 | \n",
+ " -0.001387 | \n",
+ " 5862.875775 | \n",
+ " -0.000966 | \n",
+ " 8.211402 | \n",
+ " 5880.887238 | \n",
+ " -0.004041 | \n",
+ " 3959.334316 | \n",
+ " 0.324025 | \n",
+ " 3306.352322 | \n",
+ " 0.435508 | \n",
+ " 2983.716930 | \n",
+ " 0.490592 | \n",
+ " 2762.578581 | \n",
+ " 0.528346 | \n",
+ " 2770.645622 | \n",
+ " 0.526969 | \n",
+ " 2691.311010 | \n",
+ " 0.540514 | \n",
+ " 2688.691704 | \n",
+ " 0.540961 | \n",
+ " 2693.598901 | \n",
+ " 0.540123 | \n",
+ " 2679.829203 | \n",
+ " 0.542474 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 5857.395491 | \n",
+ " -0.000030 | \n",
+ " 3478.443305 | \n",
+ " 0.406127 | \n",
+ " 3016.622857 | \n",
+ " 0.484974 | \n",
+ " 2817.417330 | \n",
+ " 0.518984 | \n",
+ " 2949.727822 | \n",
+ " 0.496395 | \n",
+ " 3027.717688 | \n",
+ " 0.483079 | \n",
+ " 3171.852993 | \n",
+ " 0.458471 | \n",
+ " 2960.568561 | \n",
+ " 0.494544 | \n",
+ " 2674.323512 | \n",
+ " 0.543414 | \n",
+ " 2693.430849 | \n",
+ " 0.540152 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 4219.124838 | \n",
+ " 0.279671 | \n",
+ " 4408.094032 | \n",
+ " 0.247408 | \n",
+ " 4260.803524 | \n",
+ " 0.272555 | \n",
+ " 4036.757481 | \n",
+ " 0.310807 | \n",
+ " 4051.713547 | \n",
+ " 0.308253 | \n",
+ " 3997.748531 | \n",
+ " 0.317467 | \n",
+ " 4059.233572 | \n",
+ " 0.306969 | \n",
+ " 3948.713206 | \n",
+ " 0.325838 | \n",
+ " 3744.098461 | \n",
+ " 0.360772 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 5862.016707 | \n",
+ " -0.000819 | \n",
+ " 3792.229582 | \n",
+ " 0.352555 | \n",
+ " 3092.988693 | \n",
+ " 0.471936 | \n",
+ " 2733.015815 | \n",
+ " 0.533394 | \n",
+ " 2564.054141 | \n",
+ " 0.562240 | \n",
+ " 2610.994432 | \n",
+ " 0.554226 | \n",
+ " 2564.381955 | \n",
+ " 0.562184 | \n",
+ " 2551.563643 | \n",
+ " 0.564373 | \n",
+ " 2545.713079 | \n",
+ " 0.565372 | \n",
+ " 2541.588137 | \n",
+ " 0.566076 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 8.487405 | \n",
+ " 2640.499813 | \n",
+ " 0.535380 | \n",
+ " 3571.052791 | \n",
+ " 0.371641 | \n",
+ " 4318.344175 | \n",
+ " 0.240148 | \n",
+ " 5017.600255 | \n",
+ " 0.117108 | \n",
+ " 5441.462496 | \n",
+ " 0.042526 | \n",
+ " 5578.882603 | \n",
+ " 0.018345 | \n",
+ " 5657.157261 | \n",
+ " 0.004572 | \n",
+ " 5614.647017 | \n",
+ " 0.012052 | \n",
+ " 5705.335037 | \n",
+ " -0.003905 | \n",
+ " 5783.179625 | \n",
+ " -0.017603 | \n",
+ " 5801.671997 | \n",
+ " -0.020857 | \n",
+ " 2496.785106 | \n",
+ " 0.560668 | \n",
+ " 3940.612956 | \n",
+ " 0.306614 | \n",
+ " 5335.869899 | \n",
+ " 0.061106 | \n",
+ " 6327.986356 | \n",
+ " -0.113466 | \n",
+ " 6817.218702 | \n",
+ " -0.199551 | \n",
+ " 6960.960204 | \n",
+ " -0.224844 | \n",
+ " 7284.148792 | \n",
+ " -0.281712 | \n",
+ " 7264.408403 | \n",
+ " -0.278238 | \n",
+ " 6351.745669 | \n",
+ " -0.117647 | \n",
+ " 5868.856530 | \n",
+ " -0.032678 | \n",
+ " 5725.785543 | \n",
+ " -0.007504 | \n",
+ " 3494.999877 | \n",
+ " 0.385023 | \n",
+ " 4069.124107 | \n",
+ " 0.284001 | \n",
+ " 4989.273260 | \n",
+ " 0.122092 | \n",
+ " 5539.634971 | \n",
+ " 0.025251 | \n",
+ " 5753.544647 | \n",
+ " -0.012388 | \n",
+ " 5721.953538 | \n",
+ " -0.006829 | \n",
+ " 6011.466936 | \n",
+ " -0.057772 | \n",
+ " 5901.583727 | \n",
+ " -0.038437 | \n",
+ " 5897.320816 | \n",
+ " -0.037687 | \n",
+ " 5938.553679 | \n",
+ " -0.044942 | \n",
+ " 5919.422152 | \n",
+ " -0.041576 | \n",
+ " 2466.857536 | \n",
+ " 0.565934 | \n",
+ " 3512.809915 | \n",
+ " 0.381889 | \n",
+ " 4466.543184 | \n",
+ " 0.214071 | \n",
+ " 5265.613075 | \n",
+ " 0.073468 | \n",
+ " 5697.985065 | \n",
+ " -0.002612 | \n",
+ " 5747.874691 | \n",
+ " -0.011390 | \n",
+ " 5760.576056 | \n",
+ " -0.013625 | \n",
+ " 5691.234177 | \n",
+ " -0.001424 | \n",
+ " 5656.583805 | \n",
+ " 0.004673 | \n",
+ " 5670.693792 | \n",
+ " 0.002190 | \n",
+ " 5691.215026 | \n",
+ " -0.001421 | \n",
+ " 8.740817 | \n",
+ " 9 | \n",
" NaN | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
" NaN | \n",
- " 2405 | \n",
- " 6.036580 | \n",
- " 1635.151982 | \n",
- " 0.728697 | \n",
- " 2928.895040 | \n",
- " 0.514040 | \n",
- " 4043.923756 | \n",
- " 0.329035 | \n",
- " 4919.486722 | \n",
- " 0.183763 | \n",
- " 5437.029551 | \n",
- " 0.097892 | \n",
- " 5901.392876 | \n",
- " 0.020846 | \n",
- " 6048.520615 | \n",
- " -0.003566 | \n",
- " 6074.659511 | \n",
- " -0.007903 | \n",
- " 6149.594281 | \n",
- " -0.020336 | \n",
- " 6175.817312 | \n",
- " -0.024687 | \n",
- " 6202.436470 | \n",
- " -0.029103 | \n",
- " 2888.523636 | \n",
- " 0.520738 | \n",
- " 3761.316620 | \n",
- " 0.375925 | \n",
- " 4957.235173 | \n",
- " 0.177500 | \n",
- " 5736.434644 | \n",
- " 0.048215 | \n",
- " 6023.733378 | \n",
- " 0.000547 | \n",
- " 6302.387576 | \n",
- " -0.045687 | \n",
- " 6410.100574 | \n",
- " -0.063559 | \n",
- " 6404.359728 | \n",
- " -0.062606 | \n",
- " 6297.330585 | \n",
- " -0.044848 | \n",
- " 6131.286306 | \n",
- " -0.017298 | \n",
- " 6027.030120 | \n",
+ " keep_all_rows | \n",
+ " 0 | \n",
+ " 100.0 | \n",
+ " 5.0 | \n",
+ " 0.33 | \n",
+ " 42.0 | \n",
+ " False | \n",
" 0.0 | \n",
- " 0.668153 | \n",
- " 0.999889 | \n",
- " 1216.244402 | \n",
- " 0.798202 | \n",
- " 2651.509022 | \n",
- " 0.560064 | \n",
- " 3485.395705 | \n",
- " 0.421706 | \n",
- " 3999.628256 | \n",
- " 0.336385 | \n",
- " 4638.982468 | \n",
- " 0.230304 | \n",
- " 5027.302770 | \n",
- " 0.165874 | \n",
- " 5386.895147 | \n",
- " 0.106211 | \n",
- " 5732.155126 | \n",
- " 0.048925 | \n",
- " 6017.858119 | \n",
- " 0.001522 | \n",
- " 6161.700389 | \n",
- " -0.022344 | \n",
- " 2328.348592 | \n",
- " 0.613682 | \n",
- " 3455.778837 | \n",
- " 0.426620 | \n",
- " 4632.400024 | \n",
- " 0.231396 | \n",
- " 5426.927997 | \n",
- " 0.099568 | \n",
- " 5750.819366 | \n",
- " 0.045829 | \n",
- " 6024.411053 | \n",
- " 0.000435 | \n",
- " 6120.464775 | \n",
- " -0.015503 | \n",
- " 6125.663086 | \n",
- " -0.016365 | \n",
- " 6092.410122 | \n",
- " -0.010848 | \n",
- " 6050.975584 | \n",
- " -0.003973 | \n",
- " 6032.751362 | \n",
- " -0.000949 | \n",
- " 10.026768 | \n",
- " 3167.314235 | \n",
- " 0.445492 | \n",
- " 3788.003075 | \n",
- " 0.336827 | \n",
- " 4752.063649 | \n",
- " 0.168047 | \n",
- " 5282.813050 | \n",
- " 0.075127 | \n",
- " 5661.928879 | \n",
- " 0.008755 | \n",
- " 5833.559426 | \n",
- " -0.021293 | \n",
- " 5865.509482 | \n",
- " -0.026887 | \n",
- " 5966.941781 | \n",
- " -0.044645 | \n",
- " 6001.779722 | \n",
- " -0.050744 | \n",
- " 6030.147576 | \n",
- " -0.055710 | \n",
- " 6067.018319 | \n",
- " -0.062165 | \n",
- " 3121.854972 | \n",
- " 0.453451 | \n",
- " 3802.338138 | \n",
- " 0.334317 | \n",
- " 4944.247196 | \n",
- " 0.134401 | \n",
- " 5658.191138 | \n",
- " 0.009409 | \n",
- " 6066.312661 | \n",
- " -0.062042 | \n",
- " 6021.472063 | \n",
- " -0.054191 | \n",
- " 6101.326312 | \n",
- " -0.068172 | \n",
- " 6090.259226 | \n",
- " -0.066234 | \n",
- " 6039.050269 | \n",
- " -0.057269 | \n",
- " 5875.871694 | \n",
- " -0.028701 | \n",
- " 5743.289993 | \n",
- " -0.005489 | \n",
- " 3565.479582 | \n",
- " 0.375784 | \n",
- " 4362.897831 | \n",
- " 0.236179 | \n",
- " 5082.947380 | \n",
- " 0.110118 | \n",
- " 5443.059555 | \n",
- " 0.047073 | \n",
- " 5747.170461 | \n",
- " -0.006169 | \n",
- " 5782.250032 | \n",
- " -0.012310 | \n",
- " 5830.867264 | \n",
- " -0.020822 | \n",
- " 5832.799073 | \n",
- " -0.021160 | \n",
- " 5886.180420 | \n",
- " -0.030505 | \n",
- " 5843.408829 | \n",
- " -0.023017 | \n",
- " 6007.922958 | \n",
- " -0.051819 | \n",
- " 3068.863830 | \n",
- " 0.462728 | \n",
- " 3818.286646 | \n",
- " 0.331525 | \n",
- " 4914.443118 | \n",
- " 0.139619 | \n",
- " 5558.586043 | \n",
- " 0.026847 | \n",
- " 5832.603810 | \n",
- " -0.021126 | \n",
- " 5784.351708 | \n",
- " -0.012678 | \n",
- " 5793.649629 | \n",
- " -0.014306 | \n",
- " 5799.895490 | \n",
- " -0.015399 | \n",
- " 5799.531819 | \n",
- " -0.015336 | \n",
- " 5783.277353 | \n",
- " -0.012490 | \n",
- " 5775.798475 | \n",
- " -0.011181 | \n",
- " 8.891757 | \n",
+ " False | \n",
+ " inbag | \n",
+ " NaN | \n",
+ " RF | \n",
+ " MDI_RF | \n",
+ " 296 | \n",
+ " 146 | \n",
+ " 10 | \n",
+ " 9 | \n",
+ " 2640.499813 | \n",
+ " 0.535380 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
" 4 | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
+ " 6 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 545 | \n",
+ " 3.896490 | \n",
+ " 1437.058926 | \n",
+ " 0.740320 | \n",
+ " 2900.469581 | \n",
+ " 0.475879 | \n",
+ " 4039.948602 | \n",
+ " 0.269972 | \n",
+ " 4745.392296 | \n",
+ " 0.142497 | \n",
+ " 5121.591713 | \n",
+ " 0.074517 | \n",
+ " 5396.791508 | \n",
+ " 0.024788 | \n",
+ " 5433.771000 | \n",
+ " 0.018105 | \n",
+ " 5483.243120 | \n",
+ " 0.009166 | \n",
+ " 5426.787503 | \n",
+ " 0.019367 | \n",
+ " 5506.799767 | \n",
+ " 0.004909 | \n",
+ " 5539.523521 | \n",
+ " -0.001004 | \n",
+ " 2751.227274 | \n",
+ " 0.502847 | \n",
+ " 4417.646065 | \n",
+ " 0.201721 | \n",
+ " 5725.073334 | \n",
+ " -0.034534 | \n",
+ " 6223.132210 | \n",
+ " -0.124534 | \n",
+ " 6394.045442 | \n",
+ " -0.155418 | \n",
+ " 6903.742081 | \n",
+ " -0.247522 | \n",
+ " 6898.005455 | \n",
+ " -0.246485 | \n",
+ " 6906.134630 | \n",
+ " -0.247954 | \n",
+ " 6621.684956 | \n",
+ " -0.196553 | \n",
+ " 6174.979003 | \n",
+ " -0.115832 | \n",
+ " 5537.963738 | \n",
+ " -0.000722 | \n",
+ " 0.018187 | \n",
+ " 0.999997 | \n",
+ " 2237.078371 | \n",
+ " 0.595755 | \n",
+ " 3839.017846 | \n",
+ " 0.306281 | \n",
+ " 4761.200794 | \n",
+ " 0.139640 | \n",
+ " 5044.732487 | \n",
+ " 0.088406 | \n",
+ " 5393.980964 | \n",
+ " 0.025296 | \n",
+ " 5405.528810 | \n",
+ " 0.023209 | \n",
+ " 5693.370483 | \n",
+ " -0.028805 | \n",
+ " 5814.666743 | \n",
+ " -0.050723 | \n",
+ " 5905.232497 | \n",
+ " -0.067089 | \n",
+ " 6105.231363 | \n",
+ " -0.103229 | \n",
+ " 2144.267875 | \n",
+ " 0.612526 | \n",
+ " 3504.405453 | \n",
+ " 0.366746 | \n",
+ " 4469.713519 | \n",
+ " 0.192313 | \n",
+ " 5063.344675 | \n",
+ " 0.085042 | \n",
+ " 5430.198772 | \n",
+ " 0.018751 | \n",
+ " 5629.508352 | \n",
+ " -0.017265 | \n",
+ " 5623.779888 | \n",
+ " -0.016230 | \n",
+ " 5604.950211 | \n",
+ " -0.012827 | \n",
+ " 5580.016962 | \n",
+ " -0.008322 | \n",
+ " 5602.884260 | \n",
+ " -0.012454 | \n",
+ " 5566.322332 | \n",
+ " -0.005847 | \n",
+ " 8.412474 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 3480.440454 | \n",
+ " 0.405786 | \n",
+ " 4428.797618 | \n",
+ " 0.243874 | \n",
+ " 5106.507299 | \n",
+ " 0.128169 | \n",
+ " 5529.201248 | \n",
+ " 0.056002 | \n",
+ " 5617.274206 | \n",
+ " 0.040966 | \n",
+ " 5691.562223 | \n",
+ " 0.028283 | \n",
+ " 5752.950476 | \n",
+ " 0.017802 | \n",
+ " 5833.262844 | \n",
+ " 0.004090 | \n",
+ " 5842.980649 | \n",
+ " 0.002431 | \n",
+ " 5889.339711 | \n",
+ " -0.005484 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 3756.267014 | \n",
+ " 0.358695 | \n",
+ " 5052.597617 | \n",
+ " 0.137373 | \n",
+ " 5888.265223 | \n",
+ " -0.005300 | \n",
+ " 6474.285892 | \n",
+ " -0.105351 | \n",
+ " 6949.460302 | \n",
+ " -0.186478 | \n",
+ " 7443.807580 | \n",
+ " -0.270877 | \n",
+ " 7688.902103 | \n",
+ " -0.312722 | \n",
+ " 7609.910506 | \n",
+ " -0.299236 | \n",
+ " 6630.493971 | \n",
+ " -0.132021 | \n",
+ " 5858.937117 | \n",
+ " -0.000293 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 3778.080730 | \n",
+ " 0.354970 | \n",
+ " 4892.289472 | \n",
+ " 0.164742 | \n",
+ " 5315.238570 | \n",
+ " 0.092532 | \n",
+ " 6000.091002 | \n",
+ " -0.024392 | \n",
+ " 5852.535489 | \n",
+ " 0.000800 | \n",
+ " 6006.108852 | \n",
+ " -0.025420 | \n",
+ " 6047.176807 | \n",
+ " -0.032431 | \n",
+ " 6096.222651 | \n",
+ " -0.040805 | \n",
+ " 6272.343509 | \n",
+ " -0.070874 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 3376.239077 | \n",
+ " 0.423576 | \n",
+ " 4407.170549 | \n",
+ " 0.247566 | \n",
+ " 5038.273900 | \n",
+ " 0.139818 | \n",
+ " 5544.234938 | \n",
+ " 0.053436 | \n",
+ " 5694.140361 | \n",
+ " 0.027842 | \n",
+ " 5835.593571 | \n",
+ " 0.003692 | \n",
+ " 5840.966477 | \n",
+ " 0.002775 | \n",
+ " 5844.553785 | \n",
+ " 0.002162 | \n",
+ " 5840.897143 | \n",
+ " 0.002787 | \n",
+ " 5862.875775 | \n",
+ " -0.000966 | \n",
+ " 8.454271 | \n",
+ " 5880.887238 | \n",
+ " -0.004041 | \n",
+ " 4289.789706 | \n",
+ " 0.267606 | \n",
+ " 3279.532842 | \n",
+ " 0.440087 | \n",
+ " 2939.586906 | \n",
+ " 0.498126 | \n",
+ " 2790.880643 | \n",
+ " 0.523514 | \n",
+ " 2724.115230 | \n",
+ " 0.534913 | \n",
+ " 2742.063657 | \n",
+ " 0.531849 | \n",
+ " 2696.681777 | \n",
+ " 0.539597 | \n",
+ " 2691.911501 | \n",
+ " 0.540411 | \n",
+ " 2709.266684 | \n",
+ " 0.537448 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 5857.395491 | \n",
+ " -0.000030 | \n",
+ " 3929.424199 | \n",
+ " 0.329131 | \n",
+ " 3133.165545 | \n",
+ " 0.465076 | \n",
+ " 3011.997732 | \n",
+ " 0.485763 | \n",
+ " 3112.891948 | \n",
+ " 0.468538 | \n",
+ " 3124.456898 | \n",
+ " 0.466563 | \n",
+ " 3230.897294 | \n",
+ " 0.448391 | \n",
+ " 3196.423926 | \n",
+ " 0.454276 | \n",
+ " 3327.729085 | \n",
+ " 0.431859 | \n",
+ " 3111.069912 | \n",
+ " 0.468849 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 4787.370582 | \n",
+ " 0.182655 | \n",
+ " 4180.157570 | \n",
+ " 0.286324 | \n",
+ " 4145.383113 | \n",
+ " 0.292261 | \n",
+ " 3919.094473 | \n",
+ " 0.330895 | \n",
+ " 3995.242224 | \n",
+ " 0.317894 | \n",
+ " 3941.916833 | \n",
+ " 0.326999 | \n",
+ " 3799.305580 | \n",
+ " 0.351347 | \n",
+ " 3577.147009 | \n",
+ " 0.389276 | \n",
+ " 3465.659544 | \n",
+ " 0.408310 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 5862.016707 | \n",
+ " -0.000819 | \n",
+ " 4157.290029 | \n",
+ " 0.290228 | \n",
+ " 3194.473744 | \n",
+ " 0.454609 | \n",
+ " 2930.804827 | \n",
+ " 0.499625 | \n",
+ " 2757.229952 | \n",
+ " 0.529260 | \n",
+ " 2661.353767 | \n",
+ " 0.545628 | \n",
+ " 2640.533322 | \n",
+ " 0.549183 | \n",
+ " 2592.707466 | \n",
+ " 0.557348 | \n",
+ " 2560.398985 | \n",
+ " 0.562864 | \n",
+ " 2567.722606 | \n",
+ " 0.561614 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 8.591958 | \n",
+ " 2640.499813 | \n",
+ " 0.535380 | \n",
+ " 3519.122896 | \n",
+ " 0.380779 | \n",
+ " 4341.295617 | \n",
+ " 0.236110 | \n",
+ " 5080.619597 | \n",
+ " 0.106019 | \n",
+ " 5361.659892 | \n",
+ " 0.056568 | \n",
+ " 5543.610178 | \n",
+ " 0.024552 | \n",
+ " 5603.054347 | \n",
+ " 0.014092 | \n",
+ " 5646.812614 | \n",
+ " 0.006392 | \n",
+ " 5742.659997 | \n",
+ " -0.010473 | \n",
+ " 5778.819764 | \n",
+ " -0.016836 | \n",
+ " 5801.671997 | \n",
+ " -0.020857 | \n",
+ " 2496.785106 | \n",
+ " 0.560668 | \n",
+ " 3747.641792 | \n",
+ " 0.340569 | \n",
+ " 4896.166926 | \n",
+ " 0.138475 | \n",
+ " 5638.775425 | \n",
+ " 0.007807 | \n",
+ " 6298.362961 | \n",
+ " -0.108254 | \n",
+ " 6810.017866 | \n",
+ " -0.198284 | \n",
+ " 7304.802884 | \n",
+ " -0.285346 | \n",
+ " 7688.411155 | \n",
+ " -0.352845 | \n",
+ " 7574.919172 | \n",
+ " -0.332875 | \n",
+ " 6629.814159 | \n",
+ " -0.166576 | \n",
+ " 5725.785543 | \n",
+ " -0.007504 | \n",
+ " 3494.999877 | \n",
+ " 0.385023 | \n",
+ " 4139.604458 | \n",
+ " 0.271599 | \n",
+ " 4808.018366 | \n",
+ " 0.153986 | \n",
+ " 5459.784944 | \n",
+ " 0.039302 | \n",
+ " 5813.890743 | \n",
+ " -0.023007 | \n",
+ " 5752.146408 | \n",
+ " -0.012142 | \n",
+ " 5743.704769 | \n",
+ " -0.010657 | \n",
+ " 5795.713241 | \n",
+ " -0.019808 | \n",
+ " 5876.811017 | \n",
+ " -0.034078 | \n",
+ " 5907.525792 | \n",
+ " -0.039483 | \n",
+ " 5919.422152 | \n",
+ " -0.041576 | \n",
+ " 2466.857536 | \n",
+ " 0.565934 | \n",
+ " 3387.295959 | \n",
+ " 0.403975 | \n",
+ " 4267.977699 | \n",
+ " 0.249011 | \n",
+ " 4967.246258 | \n",
+ " 0.125968 | \n",
+ " 5421.823682 | \n",
+ " 0.045981 | \n",
+ " 5654.847385 | \n",
+ " 0.004979 | \n",
+ " 5686.740295 | \n",
+ " -0.000633 | \n",
+ " 5670.736069 | \n",
+ " 0.002183 | \n",
+ " 5696.299307 | \n",
+ " -0.002315 | \n",
+ " 5690.972357 | \n",
+ " -0.001378 | \n",
+ " 5691.215026 | \n",
+ " -0.001421 | \n",
+ " 8.665586 | \n",
+ " 9 | \n",
" NaN | \n",
"
\n",
" \n",
- " 1 | \n",
+ " 3 | \n",
" NaN | \n",
" keep_all_rows | \n",
" 0 | \n",
@@ -697,16 +2419,579 @@
" NaN | \n",
" NaN | \n",
" RF | \n",
- " LFI_with_raw_RF | \n",
+ " TreeSHAP_RF | \n",
" 296 | \n",
" 146 | \n",
" 10 | \n",
+ " 9 | \n",
+ " 2640.499813 | \n",
+ " 0.535380 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
" 4 | \n",
- " 3167.314235 | \n",
- " 0.445492 | \n",
- " NaN | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
+ " 6 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 545 | \n",
+ " 0.353197 | \n",
+ " 1437.058926 | \n",
+ " 0.740320 | \n",
+ " 2993.318633 | \n",
+ " 0.459101 | \n",
+ " 4185.208775 | \n",
+ " 0.243723 | \n",
+ " 4928.490103 | \n",
+ " 0.109411 | \n",
+ " 5342.614052 | \n",
+ " 0.034578 | \n",
+ " 5522.340805 | \n",
+ " 0.002101 | \n",
+ " 5482.240393 | \n",
+ " 0.009347 | \n",
+ " 5577.046415 | \n",
+ " -0.007785 | \n",
+ " 5602.663206 | \n",
+ " -0.012414 | \n",
+ " 5644.869200 | \n",
+ " -0.020040 | \n",
+ " 5539.523521 | \n",
+ " -0.001004 | \n",
+ " 2751.227274 | \n",
+ " 0.502847 | \n",
+ " 4702.534726 | \n",
+ " 0.150241 | \n",
+ " 5876.798769 | \n",
+ " -0.061951 | \n",
+ " 6321.094122 | \n",
+ " -0.142236 | \n",
+ " 6672.065323 | \n",
+ " -0.205657 | \n",
+ " 6942.552888 | \n",
+ " -0.254535 | \n",
+ " 7087.736531 | \n",
+ " -0.280770 | \n",
+ " 6931.213356 | \n",
+ " -0.252486 | \n",
+ " 6571.907892 | \n",
+ " -0.187558 | \n",
+ " 6150.154721 | \n",
+ " -0.111347 | \n",
+ " 5537.963738 | \n",
+ " -0.000722 | \n",
+ " 0.018187 | \n",
+ " 0.999997 | \n",
+ " 2406.505913 | \n",
+ " 0.565139 | \n",
+ " 3694.557248 | \n",
+ " 0.332385 | \n",
+ " 4731.899147 | \n",
+ " 0.144935 | \n",
+ " 5392.714460 | \n",
+ " 0.025524 | \n",
+ " 5774.949568 | \n",
+ " -0.043546 | \n",
+ " 5789.624542 | \n",
+ " -0.046198 | \n",
+ " 5932.103010 | \n",
+ " -0.071944 | \n",
+ " 6000.631989 | \n",
+ " -0.084328 | \n",
+ " 6064.504349 | \n",
+ " -0.095869 | \n",
+ " 6105.231363 | \n",
+ " -0.103229 | \n",
+ " 2144.267875 | \n",
+ " 0.612526 | \n",
+ " 3646.878671 | \n",
+ " 0.341001 | \n",
+ " 4609.859327 | \n",
+ " 0.166988 | \n",
+ " 5163.674782 | \n",
+ " 0.066912 | \n",
+ " 5654.780863 | \n",
+ " -0.021832 | \n",
+ " 5761.998372 | \n",
+ " -0.041206 | \n",
+ " 5689.750699 | \n",
+ " -0.028151 | \n",
+ " 5675.115137 | \n",
+ " -0.025506 | \n",
+ " 5635.679423 | \n",
+ " -0.018380 | \n",
+ " 5607.887542 | \n",
+ " -0.013358 | \n",
+ " 5566.322332 | \n",
+ " -0.005847 | \n",
+ " 8.385556 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 3476.115995 | \n",
+ " 0.406525 | \n",
+ " 4606.954160 | \n",
+ " 0.213457 | \n",
+ " 5308.753320 | \n",
+ " 0.093639 | \n",
+ " 5626.772122 | \n",
+ " 0.039344 | \n",
+ " 5688.953069 | \n",
+ " 0.028728 | \n",
+ " 5665.064149 | \n",
+ " 0.032807 | \n",
+ " 5725.081827 | \n",
+ " 0.022560 | \n",
+ " 5843.531281 | \n",
+ " 0.002337 | \n",
+ " 5897.607209 | \n",
+ " -0.006895 | \n",
+ " 5889.339711 | \n",
+ " -0.005484 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 3915.996792 | \n",
+ " 0.331424 | \n",
+ " 5378.766021 | \n",
+ " 0.081686 | \n",
+ " 6371.788379 | \n",
+ " -0.087852 | \n",
+ " 6745.355899 | \n",
+ " -0.151631 | \n",
+ " 7002.600058 | \n",
+ " -0.195550 | \n",
+ " 7370.100410 | \n",
+ " -0.258293 | \n",
+ " 7607.256541 | \n",
+ " -0.298783 | \n",
+ " 7853.630412 | \n",
+ " -0.340846 | \n",
+ " 6995.518004 | \n",
+ " -0.194341 | \n",
+ " 5858.937117 | \n",
+ " -0.000293 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 3801.245390 | \n",
+ " 0.351015 | \n",
+ " 5113.264624 | \n",
+ " 0.127015 | \n",
+ " 5682.000712 | \n",
+ " 0.029915 | \n",
+ " 5921.012439 | \n",
+ " -0.010891 | \n",
+ " 5937.907776 | \n",
+ " -0.013776 | \n",
+ " 6191.459971 | \n",
+ " -0.057065 | \n",
+ " 6368.673963 | \n",
+ " -0.087320 | \n",
+ " 6357.922031 | \n",
+ " -0.085485 | \n",
+ " 6331.814400 | \n",
+ " -0.081027 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 3427.442019 | \n",
+ " 0.414835 | \n",
+ " 4648.150206 | \n",
+ " 0.206424 | \n",
+ " 5345.929388 | \n",
+ " 0.087292 | \n",
+ " 5749.058984 | \n",
+ " 0.018466 | \n",
+ " 5839.309886 | \n",
+ " 0.003058 | \n",
+ " 5852.236219 | \n",
+ " 0.000851 | \n",
+ " 5894.663360 | \n",
+ " -0.006393 | \n",
+ " 5897.950642 | \n",
+ " -0.006954 | \n",
+ " 5878.752420 | \n",
+ " -0.003676 | \n",
+ " 5862.875775 | \n",
+ " -0.000966 | \n",
+ " 8.288917 | \n",
+ " 5880.887238 | \n",
+ " -0.004041 | \n",
+ " 4146.074898 | \n",
+ " 0.292143 | \n",
+ " 3196.169721 | \n",
+ " 0.454320 | \n",
+ " 2932.924809 | \n",
+ " 0.499263 | \n",
+ " 2779.980132 | \n",
+ " 0.525375 | \n",
+ " 2787.119764 | \n",
+ " 0.524157 | \n",
+ " 2798.497189 | \n",
+ " 0.522214 | \n",
+ " 2728.217519 | \n",
+ " 0.534213 | \n",
+ " 2703.871094 | \n",
+ " 0.538370 | \n",
+ " 2668.112464 | \n",
+ " 0.544475 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 5857.395491 | \n",
+ " -0.000030 | \n",
+ " 3717.936495 | \n",
+ " 0.365239 | \n",
+ " 2915.505150 | \n",
+ " 0.502237 | \n",
+ " 2825.997755 | \n",
+ " 0.517519 | \n",
+ " 3190.456890 | \n",
+ " 0.455295 | \n",
+ " 3183.917848 | \n",
+ " 0.456411 | \n",
+ " 3062.527867 | \n",
+ " 0.477136 | \n",
+ " 3114.178465 | \n",
+ " 0.468318 | \n",
+ " 3011.890001 | \n",
+ " 0.485782 | \n",
+ " 2927.143396 | \n",
+ " 0.500250 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 5063.398973 | \n",
+ " 0.135529 | \n",
+ " 4167.734211 | \n",
+ " 0.288445 | \n",
+ " 4096.191310 | \n",
+ " 0.300659 | \n",
+ " 4113.813000 | \n",
+ " 0.297651 | \n",
+ " 4134.660106 | \n",
+ " 0.294092 | \n",
+ " 4094.226010 | \n",
+ " 0.300995 | \n",
+ " 4027.831573 | \n",
+ " 0.312330 | \n",
+ " 3914.307020 | \n",
+ " 0.331712 | \n",
+ " 3728.641417 | \n",
+ " 0.363411 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 5862.016707 | \n",
+ " -0.000819 | \n",
+ " 4012.823317 | \n",
+ " 0.314893 | \n",
+ " 3056.976176 | \n",
+ " 0.478084 | \n",
+ " 2770.118982 | \n",
+ " 0.527059 | \n",
+ " 2700.222694 | \n",
+ " 0.538992 | \n",
+ " 2668.229263 | \n",
+ " 0.544455 | \n",
+ " 2641.775898 | \n",
+ " 0.548971 | \n",
+ " 2591.837752 | \n",
+ " 0.557497 | \n",
+ " 2564.562730 | \n",
+ " 0.562154 | \n",
+ " 2554.271693 | \n",
+ " 0.563911 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 8.565224 | \n",
+ " 2640.499813 | \n",
+ " 0.535380 | \n",
+ " 3522.753563 | \n",
+ " 0.380140 | \n",
+ " 4492.754726 | \n",
+ " 0.209459 | \n",
+ " 5250.687945 | \n",
+ " 0.076094 | \n",
+ " 5540.180309 | \n",
+ " 0.025155 | \n",
+ " 5643.169395 | \n",
+ " 0.007033 | \n",
+ " 5570.930650 | \n",
+ " 0.019744 | \n",
+ " 5662.431118 | \n",
+ " 0.003644 | \n",
+ " 5773.100746 | \n",
+ " -0.015829 | \n",
+ " 5796.952295 | \n",
+ " -0.020026 | \n",
+ " 5801.671997 | \n",
+ " -0.020857 | \n",
+ " 2496.785106 | \n",
+ " 0.560668 | \n",
+ " 3874.602772 | \n",
+ " 0.318229 | \n",
+ " 5195.998249 | \n",
+ " 0.085717 | \n",
+ " 6136.557906 | \n",
+ " -0.079783 | \n",
+ " 6674.583225 | \n",
+ " -0.174453 | \n",
+ " 6842.073247 | \n",
+ " -0.203925 | \n",
+ " 7189.118672 | \n",
+ " -0.264990 | \n",
+ " 7566.606181 | \n",
+ " -0.331413 | \n",
+ " 7716.289158 | \n",
+ " -0.357751 | \n",
+ " 6944.478731 | \n",
+ " -0.221944 | \n",
+ " 5725.785543 | \n",
+ " -0.007504 | \n",
+ " 3494.999877 | \n",
+ " 0.385023 | \n",
+ " 4033.682012 | \n",
+ " 0.290237 | \n",
+ " 5034.332553 | \n",
+ " 0.114164 | \n",
+ " 5587.280407 | \n",
+ " 0.016868 | \n",
+ " 5743.479849 | \n",
+ " -0.010617 | \n",
+ " 5912.545974 | \n",
+ " -0.040366 | \n",
+ " 5896.718386 | \n",
+ " -0.037581 | \n",
+ " 6061.503398 | \n",
+ " -0.066576 | \n",
+ " 6057.537598 | \n",
+ " -0.065878 | \n",
+ " 5972.670797 | \n",
+ " -0.050945 | \n",
+ " 5919.422152 | \n",
+ " -0.041576 | \n",
+ " 2466.857536 | \n",
+ " 0.565934 | \n",
+ " 3413.979947 | \n",
+ " 0.399279 | \n",
+ " 4484.335122 | \n",
+ " 0.210941 | \n",
+ " 5200.283806 | \n",
+ " 0.084963 | \n",
+ " 5660.252160 | \n",
+ " 0.004028 | \n",
+ " 5774.580841 | \n",
+ " -0.016090 | \n",
+ " 5706.121381 | \n",
+ " -0.004044 | \n",
+ " 5733.989985 | \n",
+ " -0.008947 | \n",
+ " 5727.995769 | \n",
+ " -0.007893 | \n",
+ " 5704.121340 | \n",
+ " -0.003692 | \n",
+ " 5691.215026 | \n",
+ " -0.001421 | \n",
+ " 8.887087 | \n",
+ " 9 | \n",
" NaN | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
" NaN | \n",
+ " keep_all_rows | \n",
+ " 0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -716,6 +3001,483 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
+ " RF_plus | \n",
+ " Kernel_SHAP_RF_plus | \n",
+ " 296 | \n",
+ " 146 | \n",
+ " 10 | \n",
+ " 9 | \n",
+ " 2466.857536 | \n",
+ " 0.565934 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
+ " 4 | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
+ " 6 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 8534 | \n",
+ " 134.209250 | \n",
+ " 1437.058926 | \n",
+ " 0.740320 | \n",
+ " 2593.668426 | \n",
+ " 0.531318 | \n",
+ " 3915.160119 | \n",
+ " 0.292522 | \n",
+ " 4678.388000 | \n",
+ " 0.154605 | \n",
+ " 5028.409569 | \n",
+ " 0.091355 | \n",
+ " 5173.721429 | \n",
+ " 0.065097 | \n",
+ " 5309.990518 | \n",
+ " 0.040473 | \n",
+ " 5380.005758 | \n",
+ " 0.027821 | \n",
+ " 5537.554053 | \n",
+ " -0.000648 | \n",
+ " 5547.269238 | \n",
+ " -0.002404 | \n",
+ " 5539.523521 | \n",
+ " -0.001004 | \n",
+ " 2751.227274 | \n",
+ " 0.502847 | \n",
+ " 4131.487251 | \n",
+ " 0.253431 | \n",
+ " 5661.884034 | \n",
+ " -0.023115 | \n",
+ " 6228.786395 | \n",
+ " -0.125556 | \n",
+ " 6611.718967 | \n",
+ " -0.194752 | \n",
+ " 6898.813662 | \n",
+ " -0.246631 | \n",
+ " 6725.819832 | \n",
+ " -0.215371 | \n",
+ " 6251.340134 | \n",
+ " -0.129631 | \n",
+ " 5694.265877 | \n",
+ " -0.028967 | \n",
+ " 5427.512325 | \n",
+ " 0.019236 | \n",
+ " 5537.963738 | \n",
+ " -0.000722 | \n",
+ " 0.018187 | \n",
+ " 0.999997 | \n",
+ " 1760.246456 | \n",
+ " 0.681920 | \n",
+ " 3902.301179 | \n",
+ " 0.294845 | \n",
+ " 4786.063094 | \n",
+ " 0.135148 | \n",
+ " 5248.502766 | \n",
+ " 0.051584 | \n",
+ " 5562.326281 | \n",
+ " -0.005125 | \n",
+ " 5666.256209 | \n",
+ " -0.023905 | \n",
+ " 5825.740431 | \n",
+ " -0.052724 | \n",
+ " 5924.347912 | \n",
+ " -0.070543 | \n",
+ " 6003.463504 | \n",
+ " -0.084839 | \n",
+ " 6105.231363 | \n",
+ " -0.103229 | \n",
+ " 2144.267875 | \n",
+ " 0.612526 | \n",
+ " 3208.000445 | \n",
+ " 0.420307 | \n",
+ " 4583.943975 | \n",
+ " 0.171671 | \n",
+ " 5270.742639 | \n",
+ " 0.047565 | \n",
+ " 5593.220279 | \n",
+ " -0.010707 | \n",
+ " 5575.129386 | \n",
+ " -0.007438 | \n",
+ " 5534.621890 | \n",
+ " -0.000119 | \n",
+ " 5561.347439 | \n",
+ " -0.004948 | \n",
+ " 5576.001782 | \n",
+ " -0.007596 | \n",
+ " 5575.467267 | \n",
+ " -0.007499 | \n",
+ " 5566.322332 | \n",
+ " -0.005847 | \n",
+ " 8.385494 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 3467.889825 | \n",
+ " 0.407929 | \n",
+ " 4522.247977 | \n",
+ " 0.227919 | \n",
+ " 5062.186749 | \n",
+ " 0.135736 | \n",
+ " 5125.361953 | \n",
+ " 0.124950 | \n",
+ " 5403.866778 | \n",
+ " 0.077401 | \n",
+ " 5605.699200 | \n",
+ " 0.042942 | \n",
+ " 5672.867376 | \n",
+ " 0.031474 | \n",
+ " 5812.376227 | \n",
+ " 0.007656 | \n",
+ " 5867.281714 | \n",
+ " -0.001718 | \n",
+ " 5889.339711 | \n",
+ " -0.005484 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 4094.432088 | \n",
+ " 0.300960 | \n",
+ " 5533.852742 | \n",
+ " 0.055208 | \n",
+ " 6551.561645 | \n",
+ " -0.118545 | \n",
+ " 6861.311919 | \n",
+ " -0.171428 | \n",
+ " 7429.580019 | \n",
+ " -0.268448 | \n",
+ " 6950.073027 | \n",
+ " -0.186582 | \n",
+ " 6638.554918 | \n",
+ " -0.133397 | \n",
+ " 6173.376633 | \n",
+ " -0.053977 | \n",
+ " 5914.424323 | \n",
+ " -0.009767 | \n",
+ " 5858.937117 | \n",
+ " -0.000293 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 3734.806153 | \n",
+ " 0.362359 | \n",
+ " 5403.526760 | \n",
+ " 0.077459 | \n",
+ " 5772.297106 | \n",
+ " 0.014499 | \n",
+ " 5861.365272 | \n",
+ " -0.000708 | \n",
+ " 5670.640633 | \n",
+ " 0.031855 | \n",
+ " 5949.960467 | \n",
+ " -0.015834 | \n",
+ " 6188.619490 | \n",
+ " -0.056580 | \n",
+ " 6274.798143 | \n",
+ " -0.071293 | \n",
+ " 6275.738620 | \n",
+ " -0.071454 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 3503.461554 | \n",
+ " 0.401856 | \n",
+ " 4715.650971 | \n",
+ " 0.194899 | \n",
+ " 5419.732700 | \n",
+ " 0.074692 | \n",
+ " 5622.243735 | \n",
+ " 0.040117 | \n",
+ " 5756.416526 | \n",
+ " 0.017210 | \n",
+ " 5820.147416 | \n",
+ " 0.006329 | \n",
+ " 5828.767393 | \n",
+ " 0.004858 | \n",
+ " 5829.349967 | \n",
+ " 0.004758 | \n",
+ " 5860.065543 | \n",
+ " -0.000486 | \n",
+ " 5862.875775 | \n",
+ " -0.000966 | \n",
+ " 8.337007 | \n",
+ " 5880.887238 | \n",
+ " -0.004041 | \n",
+ " 4016.926503 | \n",
+ " 0.314192 | \n",
+ " 3239.020925 | \n",
+ " 0.447004 | \n",
+ " 3018.744971 | \n",
+ " 0.484611 | \n",
+ " 2833.885025 | \n",
+ " 0.516172 | \n",
+ " 2762.022798 | \n",
+ " 0.528441 | \n",
+ " 2744.015733 | \n",
+ " 0.531516 | \n",
+ " 2727.651489 | \n",
+ " 0.534310 | \n",
+ " 2708.425989 | \n",
+ " 0.537592 | \n",
+ " 2670.802856 | \n",
+ " 0.544015 | \n",
+ " 2679.064560 | \n",
+ " 0.542605 | \n",
+ " 5857.395491 | \n",
+ " -0.000030 | \n",
+ " 3492.276791 | \n",
+ " 0.403765 | \n",
+ " 2955.758856 | \n",
+ " 0.495365 | \n",
+ " 2686.976279 | \n",
+ " 0.541254 | \n",
+ " 2958.235627 | \n",
+ " 0.494942 | \n",
+ " 3127.977014 | \n",
+ " 0.465962 | \n",
+ " 3240.538911 | \n",
+ " 0.446745 | \n",
+ " 2845.779006 | \n",
+ " 0.514142 | \n",
+ " 2691.562055 | \n",
+ " 0.540471 | \n",
+ " 2656.686546 | \n",
+ " 0.546425 | \n",
+ " 2565.576138 | \n",
+ " 0.561981 | \n",
+ " 6281.215482 | \n",
+ " -0.072389 | \n",
+ " 4525.469962 | \n",
+ " 0.227369 | \n",
+ " 4331.440232 | \n",
+ " 0.260496 | \n",
+ " 4152.517996 | \n",
+ " 0.291043 | \n",
+ " 3953.368818 | \n",
+ " 0.325043 | \n",
+ " 4132.817470 | \n",
+ " 0.294406 | \n",
+ " 4087.757952 | \n",
+ " 0.302099 | \n",
+ " 4091.054772 | \n",
+ " 0.301536 | \n",
+ " 3889.639927 | \n",
+ " 0.335924 | \n",
+ " 3682.165264 | \n",
+ " 0.371346 | \n",
+ " 3557.841426 | \n",
+ " 0.392572 | \n",
+ " 5862.016707 | \n",
+ " -0.000819 | \n",
+ " 3840.160816 | \n",
+ " 0.344371 | \n",
+ " 3031.188396 | \n",
+ " 0.482487 | \n",
+ " 2722.696131 | \n",
+ " 0.535156 | \n",
+ " 2616.745973 | \n",
+ " 0.553244 | \n",
+ " 2595.289374 | \n",
+ " 0.556908 | \n",
+ " 2591.050321 | \n",
+ " 0.557631 | \n",
+ " 2568.578591 | \n",
+ " 0.561468 | \n",
+ " 2566.086550 | \n",
+ " 0.561893 | \n",
+ " 2533.869882 | \n",
+ " 0.567394 | \n",
+ " 2541.457199 | \n",
+ " 0.566098 | \n",
+ " 8.649657 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -804,1103 +3566,9 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
- " 2405 | \n",
- " 6.758458 | \n",
- " 1635.151982 | \n",
- " 0.728697 | \n",
- " 3021.720386 | \n",
- " 0.498639 | \n",
- " 4123.708913 | \n",
- " 0.315798 | \n",
- " 4906.024069 | \n",
- " 0.185996 | \n",
- " 5541.504254 | \n",
- " 0.080558 | \n",
- " 5961.706039 | \n",
- " 0.010839 | \n",
- " 6122.232814 | \n",
- " -0.015796 | \n",
- " 6184.281735 | \n",
- " -0.026091 | \n",
- " 6199.593162 | \n",
- " -0.028632 | \n",
- " 6192.776084 | \n",
- " -0.027500 | \n",
- " 6202.436470 | \n",
- " -0.029103 | \n",
- " 2888.523636 | \n",
- " 0.520738 | \n",
- " 3916.706467 | \n",
- " 0.350143 | \n",
- " 5015.669338 | \n",
- " 0.167804 | \n",
- " 5721.361272 | \n",
- " 0.050716 | \n",
- " 6139.722264 | \n",
- " -0.018698 | \n",
- " 6341.303427 | \n",
- " -0.052144 | \n",
- " 6388.554668 | \n",
- " -0.059984 | \n",
- " 6433.855484 | \n",
- " -0.067500 | \n",
- " 6443.171782 | \n",
- " -0.069046 | \n",
- " 6298.161514 | \n",
- " -0.044986 | \n",
- " 6027.030120 | \n",
- " 0.0 | \n",
- " 0.668153 | \n",
- " 0.999889 | \n",
- " 1208.211458 | \n",
- " 0.799535 | \n",
- " 2624.721798 | \n",
- " 0.564508 | \n",
- " 3463.798074 | \n",
- " 0.425289 | \n",
- " 4048.620645 | \n",
- " 0.328256 | \n",
- " 4674.750775 | \n",
- " 0.224369 | \n",
- " 4920.398751 | \n",
- " 0.183611 | \n",
- " 5196.455731 | \n",
- " 0.137808 | \n",
- " 5560.146803 | \n",
- " 0.077465 | \n",
- " 5842.122436 | \n",
- " 0.030680 | \n",
- " 6161.700389 | \n",
- " -0.022344 | \n",
- " 2328.348592 | \n",
- " 0.613682 | \n",
- " 3586.105224 | \n",
- " 0.404996 | \n",
- " 4700.756327 | \n",
- " 0.220054 | \n",
- " 5412.704307 | \n",
- " 0.101928 | \n",
- " 5855.402714 | \n",
- " 0.028476 | \n",
- " 6061.293311 | \n",
- " -0.005685 | \n",
- " 6135.493568 | \n",
- " -0.017996 | \n",
- " 6186.457881 | \n",
- " -0.026452 | \n",
- " 6171.165504 | \n",
- " -0.023915 | \n",
- " 6102.377688 | \n",
- " -0.012502 | \n",
- " 6032.751362 | \n",
- " -0.000949 | \n",
- " 10.083984 | \n",
- " 3167.314235 | \n",
- " 0.445492 | \n",
- " 3827.691114 | \n",
- " 0.329878 | \n",
- " 4578.262051 | \n",
- " 0.198474 | \n",
- " 5044.353110 | \n",
- " 0.116875 | \n",
- " 5456.091373 | \n",
- " 0.044791 | \n",
- " 5793.795173 | \n",
- " -0.014331 | \n",
- " 6010.746038 | \n",
- " -0.052313 | \n",
- " 6049.385658 | \n",
- " -0.059078 | \n",
- " 5998.481445 | \n",
- " -0.050166 | \n",
- " 6036.697699 | \n",
- " -0.056857 | \n",
- " 6067.018319 | \n",
- " -0.062165 | \n",
- " 3121.854972 | \n",
- " 0.453451 | \n",
- " 3803.232973 | \n",
- " 0.334160 | \n",
- " 4703.872125 | \n",
- " 0.176484 | \n",
- " 5324.761627 | \n",
- " 0.067783 | \n",
- " 5773.709727 | \n",
- " -0.010815 | \n",
- " 5977.826552 | \n",
- " -0.046550 | \n",
- " 5986.809965 | \n",
- " -0.048123 | \n",
- " 5983.111169 | \n",
- " -0.047475 | \n",
- " 5939.508997 | \n",
- " -0.039842 | \n",
- " 5810.251492 | \n",
- " -0.017212 | \n",
- " 5743.289993 | \n",
- " -0.005489 | \n",
- " 3565.479582 | \n",
- " 0.375784 | \n",
- " 4417.125378 | \n",
- " 0.226685 | \n",
- " 5059.030994 | \n",
- " 0.114305 | \n",
- " 5123.918062 | \n",
- " 0.102945 | \n",
- " 5524.767115 | \n",
- " 0.032768 | \n",
- " 5776.289705 | \n",
- " -0.011267 | \n",
- " 6083.961808 | \n",
- " -0.065131 | \n",
- " 5755.751419 | \n",
- " -0.007671 | \n",
- " 5791.839463 | \n",
- " -0.013989 | \n",
- " 5875.728030 | \n",
- " -0.028676 | \n",
- " 6007.922958 | \n",
- " -0.051819 | \n",
- " 3068.863830 | \n",
- " 0.462728 | \n",
- " 3824.162442 | \n",
- " 0.330496 | \n",
- " 4707.799112 | \n",
- " 0.175796 | \n",
- " 5259.040670 | \n",
- " 0.079289 | \n",
- " 5575.386841 | \n",
- " 0.023906 | \n",
- " 5723.134442 | \n",
- " -0.001961 | \n",
- " 5771.443274 | \n",
- " -0.010418 | \n",
- " 5830.381002 | \n",
- " -0.020737 | \n",
- " 5789.080541 | \n",
- " -0.013506 | \n",
- " 5778.531386 | \n",
- " -0.011659 | \n",
- " 5775.798475 | \n",
- " -0.011181 | \n",
- " 8.881537 | \n",
- " 4 | \n",
" NaN | \n",
- "
\n",
- " \n",
- " 2 | \n",
- " NaN | \n",
- " keep_all_rows | \n",
- " 0 | \n",
- " 100.0 | \n",
- " 5.0 | \n",
- " 0.33 | \n",
- " 42.0 | \n",
- " False | \n",
- " 0.0 | \n",
- " False | \n",
- " inbag | \n",
- " NaN | \n",
- " RF | \n",
- " MDI_RF | \n",
- " 296 | \n",
- " 146 | \n",
- " 10 | \n",
- " 4 | \n",
- " 3167.314235 | \n",
- " 0.445492 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 2405 | \n",
- " 2.749065 | \n",
- " 1635.151982 | \n",
- " 0.728697 | \n",
- " 3133.874535 | \n",
- " 0.480030 | \n",
- " 4208.266058 | \n",
- " 0.301768 | \n",
- " 5012.797456 | \n",
- " 0.168281 | \n",
- " 5621.910172 | \n",
- " 0.067217 | \n",
- " 6002.738896 | \n",
- " 0.004030 | \n",
- " 6121.457849 | \n",
- " -0.015667 | \n",
- " 6210.278943 | \n",
- " -0.030404 | \n",
- " 6247.690750 | \n",
- " -0.036612 | \n",
- " 6250.071403 | \n",
- " -0.037007 | \n",
- " 6202.436470 | \n",
- " -0.029103 | \n",
- " 2888.523636 | \n",
- " 0.520738 | \n",
- " 3914.109435 | \n",
- " 0.350574 | \n",
- " 4885.192723 | \n",
- " 0.189453 | \n",
- " 5492.817224 | \n",
- " 0.088636 | \n",
- " 6031.489112 | \n",
- " -0.000740 | \n",
- " 6247.694137 | \n",
- " -0.036612 | \n",
- " 6325.959184 | \n",
- " -0.049598 | \n",
- " 6326.214645 | \n",
- " -0.049640 | \n",
- " 6208.409712 | \n",
- " -0.030094 | \n",
- " 6127.752193 | \n",
- " -0.016712 | \n",
- " 6027.030120 | \n",
- " 0.0 | \n",
- " 0.668153 | \n",
- " 0.999889 | \n",
- " 1213.928121 | \n",
- " 0.798586 | \n",
- " 2602.100460 | \n",
- " 0.568262 | \n",
- " 3578.727889 | \n",
- " 0.406220 | \n",
- " 4127.285053 | \n",
- " 0.315204 | \n",
- " 4494.619078 | \n",
- " 0.254256 | \n",
- " 5001.728634 | \n",
- " 0.170117 | \n",
- " 5463.751185 | \n",
- " 0.093459 | \n",
- " 5817.996707 | \n",
- " 0.034683 | \n",
- " 6094.716095 | \n",
- " -0.011230 | \n",
- " 6161.700389 | \n",
- " -0.022344 | \n",
- " 2328.348592 | \n",
- " 0.613682 | \n",
- " 3618.673346 | \n",
- " 0.399593 | \n",
- " 4672.741484 | \n",
- " 0.224702 | \n",
- " 5318.471574 | \n",
- " 0.117563 | \n",
- " 5765.457023 | \n",
- " 0.043400 | \n",
- " 6003.824735 | \n",
- " 0.003850 | \n",
- " 6113.418631 | \n",
- " -0.014334 | \n",
- " 6179.035357 | \n",
- " -0.025221 | \n",
- " 6148.517487 | \n",
- " -0.020157 | \n",
- " 6098.941000 | \n",
- " -0.011931 | \n",
- " 6032.751362 | \n",
- " -0.000949 | \n",
- " 10.183294 | \n",
- " 3167.314235 | \n",
- " 0.445492 | \n",
- " 3911.846966 | \n",
- " 0.315145 | \n",
- " 4673.293043 | \n",
- " 0.181837 | \n",
- " 5165.809068 | \n",
- " 0.095611 | \n",
- " 5579.673507 | \n",
- " 0.023155 | \n",
- " 5866.425027 | \n",
- " -0.027047 | \n",
- " 5899.293811 | \n",
- " -0.032801 | \n",
- " 6021.113226 | \n",
- " -0.054128 | \n",
- " 6042.816515 | \n",
- " -0.057928 | \n",
- " 6017.320805 | \n",
- " -0.053464 | \n",
- " 6067.018319 | \n",
- " -0.062165 | \n",
- " 3121.854972 | \n",
- " 0.453451 | \n",
- " 3782.799439 | \n",
- " 0.337738 | \n",
- " 4640.935068 | \n",
- " 0.187502 | \n",
- " 5146.024758 | \n",
- " 0.099075 | \n",
- " 5560.543096 | \n",
- " 0.026504 | \n",
- " 5746.434317 | \n",
- " -0.006040 | \n",
- " 5832.336892 | \n",
- " -0.021079 | \n",
- " 5952.085807 | \n",
- " -0.042044 | \n",
- " 5999.332220 | \n",
- " -0.050315 | \n",
- " 5843.222894 | \n",
- " -0.022985 | \n",
- " 5743.289993 | \n",
- " -0.005489 | \n",
- " 3565.479582 | \n",
- " 0.375784 | \n",
- " 4491.207741 | \n",
- " 0.213715 | \n",
- " 5325.002424 | \n",
- " 0.067741 | \n",
- " 5404.375561 | \n",
- " 0.053845 | \n",
- " 6105.030874 | \n",
- " -0.068820 | \n",
- " 6161.928219 | \n",
- " -0.078781 | \n",
- " 6084.476971 | \n",
- " -0.065222 | \n",
- " 6072.037858 | \n",
- " -0.063044 | \n",
- " 6164.297845 | \n",
- " -0.079196 | \n",
- " 6121.536055 | \n",
- " -0.071710 | \n",
- " 6007.922958 | \n",
- " -0.051819 | \n",
- " 3068.863830 | \n",
- " 0.462728 | \n",
- " 3827.072282 | \n",
- " 0.329987 | \n",
- " 4716.561876 | \n",
- " 0.174262 | \n",
- " 5153.033770 | \n",
- " 0.097848 | \n",
- " 5434.084925 | \n",
- " 0.048644 | \n",
- " 5554.591693 | \n",
- " 0.027546 | \n",
- " 5635.787161 | \n",
- " 0.013331 | \n",
- " 5763.684469 | \n",
- " -0.009060 | \n",
- " 5807.287765 | \n",
- " -0.016694 | \n",
- " 5761.554160 | \n",
- " -0.008687 | \n",
- " 5775.798475 | \n",
- " -0.011181 | \n",
- " 8.914796 | \n",
- " 4 | \n",
- " NaN | \n",
- "
\n",
- " \n",
- " 3 | \n",
- " NaN | \n",
- " keep_all_rows | \n",
- " 0 | \n",
- " 100.0 | \n",
- " 5.0 | \n",
- " 0.33 | \n",
- " 42.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " RF | \n",
- " TreeSHAP_RF | \n",
- " 296 | \n",
- " 146 | \n",
- " 10 | \n",
- " 4 | \n",
- " 3167.314235 | \n",
- " 0.445492 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 2405 | \n",
- " 0.413684 | \n",
- " 1635.151982 | \n",
- " 0.728697 | \n",
- " 3195.234603 | \n",
- " 0.469849 | \n",
- " 4374.383756 | \n",
- " 0.274206 | \n",
- " 5218.143321 | \n",
- " 0.134210 | \n",
- " 5792.052146 | \n",
- " 0.038987 | \n",
- " 6124.433170 | \n",
- " -0.016161 | \n",
- " 6182.621856 | \n",
- " -0.025816 | \n",
- " 6213.795448 | \n",
- " -0.030988 | \n",
- " 6220.357930 | \n",
- " -0.032077 | \n",
- " 6228.987740 | \n",
- " -0.033509 | \n",
- " 6202.436470 | \n",
- " -0.029103 | \n",
- " 2888.523636 | \n",
- " 0.520738 | \n",
- " 4024.382264 | \n",
- " 0.332278 | \n",
- " 5102.326251 | \n",
- " 0.153426 | \n",
- " 5740.581038 | \n",
- " 0.047527 | \n",
- " 6321.322530 | \n",
- " -0.048829 | \n",
- " 6555.449924 | \n",
- " -0.087675 | \n",
- " 6510.868650 | \n",
- " -0.080278 | \n",
- " 6390.723824 | \n",
- " -0.060344 | \n",
- " 6225.389065 | \n",
- " -0.032912 | \n",
- " 6088.198905 | \n",
- " -0.010149 | \n",
- " 6027.030120 | \n",
- " 0.0 | \n",
- " 0.668153 | \n",
- " 0.999889 | \n",
- " 1110.645464 | \n",
- " 0.815723 | \n",
- " 2856.413683 | \n",
- " 0.526066 | \n",
- " 3690.510793 | \n",
- " 0.387673 | \n",
- " 4235.765848 | \n",
- " 0.297205 | \n",
- " 4872.452681 | \n",
- " 0.191567 | \n",
- " 5242.038979 | \n",
- " 0.130245 | \n",
- " 5452.423985 | \n",
- " 0.095338 | \n",
- " 5587.003451 | \n",
- " 0.073009 | \n",
- " 6176.740303 | \n",
- " -0.024840 | \n",
- " 6161.700389 | \n",
- " -0.022344 | \n",
- " 2328.348592 | \n",
- " 0.613682 | \n",
- " 3681.820673 | \n",
- " 0.389115 | \n",
- " 4820.261610 | \n",
- " 0.200226 | \n",
- " 5537.866064 | \n",
- " 0.081162 | \n",
- " 5995.550352 | \n",
- " 0.005223 | \n",
- " 6243.577365 | \n",
- " -0.035929 | \n",
- " 6221.975848 | \n",
- " -0.032345 | \n",
- " 6190.922138 | \n",
- " -0.027193 | \n",
- " 6150.480056 | \n",
- " -0.020483 | \n",
- " 6103.170216 | \n",
- " -0.012633 | \n",
- " 6032.751362 | \n",
- " -0.000949 | \n",
- " 9.835077 | \n",
- " 3167.314235 | \n",
- " 0.445492 | \n",
- " 3775.838507 | \n",
- " 0.338956 | \n",
- " 4633.157541 | \n",
- " 0.188864 | \n",
- " 5247.502613 | \n",
- " 0.081309 | \n",
- " 5637.322633 | \n",
- " 0.013063 | \n",
- " 5960.763458 | \n",
- " -0.043563 | \n",
- " 5977.057139 | \n",
- " -0.046415 | \n",
- " 6028.927315 | \n",
- " -0.055496 | \n",
- " 6074.807174 | \n",
- " -0.063529 | \n",
- " 6086.136079 | \n",
- " -0.065512 | \n",
- " 6067.018319 | \n",
- " -0.062165 | \n",
- " 3121.854972 | \n",
- " 0.453451 | \n",
- " 3739.288445 | \n",
- " 0.345355 | \n",
- " 4678.676433 | \n",
- " 0.180895 | \n",
- " 5452.652247 | \n",
- " 0.045393 | \n",
- " 5808.699092 | \n",
- " -0.016941 | \n",
- " 6069.614343 | \n",
- " -0.062620 | \n",
- " 5915.356963 | \n",
- " -0.035613 | \n",
- " 6006.034824 | \n",
- " -0.051489 | \n",
- " 5993.584111 | \n",
- " -0.049309 | \n",
- " 5835.219347 | \n",
- " -0.021584 | \n",
- " 5743.289993 | \n",
- " -0.005489 | \n",
- " 3565.479582 | \n",
- " 0.375784 | \n",
- " 4237.764376 | \n",
- " 0.258086 | \n",
- " 5120.520406 | \n",
- " 0.103540 | \n",
- " 5318.162829 | \n",
- " 0.068939 | \n",
- " 5673.859855 | \n",
- " 0.006666 | \n",
- " 6080.111206 | \n",
- " -0.064457 | \n",
- " 6056.849952 | \n",
- " -0.060385 | \n",
- " 6114.234944 | \n",
- " -0.070431 | \n",
- " 6259.056809 | \n",
- " -0.095786 | \n",
- " 6129.607419 | \n",
- " -0.073123 | \n",
- " 6007.922958 | \n",
- " -0.051819 | \n",
- " 3068.863830 | \n",
- " 0.462728 | \n",
- " 3732.654148 | \n",
- " 0.346517 | \n",
- " 4726.437509 | \n",
- " 0.172533 | \n",
- " 5427.336730 | \n",
- " 0.049825 | \n",
- " 5680.278030 | \n",
- " 0.005542 | \n",
- " 5833.784358 | \n",
- " -0.021332 | \n",
- " 5714.152885 | \n",
- " -0.000388 | \n",
- " 5797.828571 | \n",
- " -0.015038 | \n",
- " 5811.450208 | \n",
- " -0.017422 | \n",
- " 5807.028565 | \n",
- " -0.016648 | \n",
- " 5775.798475 | \n",
- " -0.011181 | \n",
- " 8.867040 | \n",
- " 4 | \n",
- " NaN | \n",
- "
\n",
- " \n",
- " 4 | \n",
- " NaN | \n",
- " keep_all_rows | \n",
- " 0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " RF_plus | \n",
- " Kernel_SHAP_RF_plus | \n",
- " 296 | \n",
- " 100 | \n",
- " 10 | \n",
- " 4 | \n",
- " 3068.863830 | \n",
- " 0.462728 | \n",
- " 19.0 | \n",
- " 18.0 | \n",
- " 119.0 | \n",
- " 77.0 | \n",
- " 71.0 | \n",
- " 103.0 | \n",
- " 33.0 | \n",
- " 126.0 | \n",
- " 48.0 | \n",
- " 36.0 | \n",
- " 59.0 | \n",
- " 49.0 | \n",
- " 62.0 | \n",
- " 42.0 | \n",
- " 13.0 | \n",
- " 82.0 | \n",
- " 22.0 | \n",
- " 123.0 | \n",
- " 75.0 | \n",
- " 137.0 | \n",
- " 134.0 | \n",
- " 38.0 | \n",
- " 2.0 | \n",
- " 79.0 | \n",
- " 138.0 | \n",
- " 88.0 | \n",
- " 54.0 | \n",
- " 55.0 | \n",
- " 84.0 | \n",
- " 50.0 | \n",
- " 114.0 | \n",
- " 144.0 | \n",
- " 7.0 | \n",
- " 53.0 | \n",
- " 5.0 | \n",
- " 124.0 | \n",
- " 104.0 | \n",
- " 44.0 | \n",
- " 60.0 | \n",
- " 99.0 | \n",
- " 93.0 | \n",
- " 112.0 | \n",
- " 128.0 | \n",
- " 85.0 | \n",
- " 76.0 | \n",
- " 25.0 | \n",
- " 92.0 | \n",
- " 86.0 | \n",
- " 127.0 | \n",
- " 115.0 | \n",
- " 41.0 | \n",
- " 97.0 | \n",
- " 113.0 | \n",
- " 118.0 | \n",
- " 135.0 | \n",
- " 101.0 | \n",
- " 8.0 | \n",
- " 27.0 | \n",
- " 72.0 | \n",
- " 94.0 | \n",
- " 133.0 | \n",
- " 43.0 | \n",
- " 120.0 | \n",
- " 51.0 | \n",
- " 132.0 | \n",
- " 61.0 | \n",
- " 83.0 | \n",
- " 32.0 | \n",
- " 45.0 | \n",
- " 95.0 | \n",
- " 30.0 | \n",
- " 31.0 | \n",
- " 90.0 | \n",
- " 129.0 | \n",
- " 100.0 | \n",
- " 96.0 | \n",
- " 14.0 | \n",
- " 39.0 | \n",
- " 80.0 | \n",
- " 56.0 | \n",
- " 35.0 | \n",
- " 139.0 | \n",
- " 16.0 | \n",
- " 70.0 | \n",
- " 46.0 | \n",
- " 69.0 | \n",
- " 6.0 | \n",
- " 23.0 | \n",
- " 52.0 | \n",
- " 29.0 | \n",
- " 15.0 | \n",
- " 66.0 | \n",
- " 68.0 | \n",
- " 37.0 | \n",
- " 64.0 | \n",
- " 17.0 | \n",
- " 4.0 | \n",
- " 145.0 | \n",
- " 47.0 | \n",
- " 63.0 | \n",
- " 6733 | \n",
- " 272.584633 | \n",
- " 1635.151982 | \n",
- " 0.728697 | \n",
- " 3010.018440 | \n",
- " 0.500580 | \n",
- " 4081.594103 | \n",
- " 0.322785 | \n",
- " 4871.540333 | \n",
- " 0.191718 | \n",
- " 5427.925117 | \n",
- " 0.099403 | \n",
- " 5806.229855 | \n",
- " 0.036635 | \n",
- " 5968.959854 | \n",
- " 0.009635 | \n",
- " 6009.615524 | \n",
- " 0.002889 | \n",
- " 6028.684646 | \n",
- " -0.000275 | \n",
- " 6089.516761 | \n",
- " -0.010368 | \n",
- " 6202.436470 | \n",
- " -0.029103 | \n",
- " 2888.523636 | \n",
- " 0.520738 | \n",
- " 3867.089557 | \n",
- " 0.358376 | \n",
- " 4936.004551 | \n",
- " 0.181022 | \n",
- " 5618.567424 | \n",
- " 0.067772 | \n",
- " 5961.929743 | \n",
- " 0.010801 | \n",
- " 6114.847766 | \n",
- " -0.014571 | \n",
- " 6198.656398 | \n",
- " -0.028476 | \n",
- " 6287.859301 | \n",
- " -0.043277 | \n",
- " 6274.965297 | \n",
- " -0.041137 | \n",
- " 6153.972043 | \n",
- " -0.021062 | \n",
- " 6027.030120 | \n",
- " 0.0 | \n",
- " 0.668153 | \n",
- " 0.999889 | \n",
- " 1227.836013 | \n",
- " 0.796278 | \n",
- " 2655.454874 | \n",
- " 0.559409 | \n",
- " 3489.393571 | \n",
- " 0.421043 | \n",
- " 4007.950448 | \n",
- " 0.335004 | \n",
- " 4607.906326 | \n",
- " 0.235460 | \n",
- " 5426.288241 | \n",
- " 0.099675 | \n",
- " 5628.621190 | \n",
- " 0.066104 | \n",
- " 5785.556238 | \n",
- " 0.040065 | \n",
- " 5987.542309 | \n",
- " 0.006552 | \n",
- " 6161.700389 | \n",
- " -0.022344 | \n",
- " 2328.348592 | \n",
- " 0.613682 | \n",
- " 3556.013929 | \n",
- " 0.409989 | \n",
- " 4662.131533 | \n",
- " 0.226463 | \n",
- " 5368.597563 | \n",
- " 0.109247 | \n",
- " 5731.046785 | \n",
- " 0.049109 | \n",
- " 5894.048153 | \n",
- " 0.022064 | \n",
- " 5960.296484 | \n",
- " 0.011072 | \n",
- " 6029.442460 | \n",
- " -0.000400 | \n",
- " 6041.139850 | \n",
- " -0.002341 | \n",
- " 6036.782692 | \n",
- " -0.001618 | \n",
- " 6032.751362 | \n",
- " -0.000949 | \n",
- " 9.809540 | \n",
- " 3476.788124 | \n",
- " 0.417422 | \n",
- " 4194.571341 | \n",
- " 0.297148 | \n",
- " 5334.974847 | \n",
- " 0.106060 | \n",
- " 5596.675389 | \n",
- " 0.062209 | \n",
- " 5937.622020 | \n",
- " 0.005079 | \n",
- " 6111.152277 | \n",
- " -0.023998 | \n",
- " 6143.624744 | \n",
- " -0.029439 | \n",
- " 6163.867887 | \n",
- " -0.032831 | \n",
- " 6244.000528 | \n",
- " -0.046258 | \n",
- " 6396.107074 | \n",
- " -0.071746 | \n",
- " 6465.545412 | \n",
- " -0.083381 | \n",
- " 3465.585233 | \n",
- " 0.419299 | \n",
- " 4161.596525 | \n",
- " 0.302674 | \n",
- " 5338.566511 | \n",
- " 0.105458 | \n",
- " 5866.474772 | \n",
- " 0.017001 | \n",
- " 6058.949364 | \n",
- " -0.015251 | \n",
- " 6186.505044 | \n",
- " -0.036624 | \n",
- " 6078.148133 | \n",
- " -0.018468 | \n",
- " 6079.932688 | \n",
- " -0.018767 | \n",
- " 6124.462336 | \n",
- " -0.026228 | \n",
- " 6098.814817 | \n",
- " -0.021931 | \n",
- " 6050.073529 | \n",
- " -0.013764 | \n",
- " 3931.667854 | \n",
- " 0.341201 | \n",
- " 4787.549007 | \n",
- " 0.197788 | \n",
- " 5654.969990 | \n",
- " 0.052441 | \n",
- " 5475.757988 | \n",
- " 0.082470 | \n",
- " 5690.431182 | \n",
- " 0.046499 | \n",
- " 5921.843788 | \n",
- " 0.007723 | \n",
- " 5940.795730 | \n",
- " 0.004547 | \n",
- " 6009.317532 | \n",
- " -0.006934 | \n",
- " 6309.394957 | \n",
- " -0.057216 | \n",
- " 6453.157959 | \n",
- " -0.081305 | \n",
- " 6395.094041 | \n",
- " -0.071576 | \n",
- " 3392.891623 | \n",
- " 0.431480 | \n",
- " 4191.710491 | \n",
- " 0.297628 | \n",
- " 5399.696626 | \n",
- " 0.095215 | \n",
- " 5851.776337 | \n",
- " 0.019464 | \n",
- " 6018.755220 | \n",
- " -0.008516 | \n",
- " 6071.573392 | \n",
- " -0.017366 | \n",
- " 6010.857279 | \n",
- " -0.007192 | \n",
- " 6042.684405 | \n",
- " -0.012525 | \n",
- " 6090.457960 | \n",
- " -0.020530 | \n",
- " 6081.173795 | \n",
- " -0.018975 | \n",
- " 6099.151078 | \n",
- " -0.021987 | \n",
- " 8.382616 | \n",
- " 4 | \n",
- " RandomForestRegressor(max_features=0.33, min_s... | \n",
+ " 9 | \n",
+ " RandomForestRegressor(max_features=0.33, min_s... | \n",
"
\n",
" \n",
" ... | \n",
@@ -2206,6 +3874,284 @@
" ... | \n",
" ... | \n",
" ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
"
\n",
" \n",
" 65 | \n",
@@ -2226,18 +4172,1158 @@
" 296 | \n",
" 146 | \n",
" 10 | \n",
+ " 10 | \n",
+ " 3317.655397 | \n",
+ " 0.470632 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
+ " 4 | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
" 6 | \n",
- " 3072.457734 | \n",
- " 0.448450 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 3650 | \n",
+ " 4.258376 | \n",
+ " 1438.855135 | \n",
+ " 0.742201 | \n",
+ " 2678.898633 | \n",
+ " 0.520023 | \n",
+ " 4165.208912 | \n",
+ " 0.253722 | \n",
+ " 4813.668323 | \n",
+ " 0.137538 | \n",
+ " 5176.160990 | \n",
+ " 0.072590 | \n",
+ " 5445.473321 | \n",
+ " 0.024338 | \n",
+ " 5445.779737 | \n",
+ " 0.024283 | \n",
+ " 5590.734303 | \n",
+ " -0.001689 | \n",
+ " 5562.477277 | \n",
+ " 0.003374 | \n",
+ " 5710.567724 | \n",
+ " -0.023159 | \n",
+ " 5687.565590 | \n",
+ " -0.019038 | \n",
+ " 2738.215621 | \n",
+ " 0.509396 | \n",
+ " 3827.443185 | \n",
+ " 0.314239 | \n",
+ " 5227.500681 | \n",
+ " 0.063392 | \n",
+ " 5931.959208 | \n",
+ " -0.062826 | \n",
+ " 6180.587308 | \n",
+ " -0.107372 | \n",
+ " 6571.688377 | \n",
+ " -0.177446 | \n",
+ " 6367.528123 | \n",
+ " -0.140866 | \n",
+ " 6390.940437 | \n",
+ " -0.145061 | \n",
+ " 6051.307223 | \n",
+ " -0.084209 | \n",
+ " 5933.424152 | \n",
+ " -0.063088 | \n",
+ " 5589.440875 | \n",
+ " -0.001457 | \n",
+ " 0.097250 | \n",
+ " 0.999983 | \n",
+ " 1409.122866 | \n",
+ " 0.747528 | \n",
+ " 3062.737215 | \n",
+ " 0.451251 | \n",
+ " 4143.180980 | \n",
+ " 0.257669 | \n",
+ " 4973.750342 | \n",
+ " 0.108856 | \n",
+ " 5579.904958 | \n",
+ " 0.000252 | \n",
+ " 5919.620840 | \n",
+ " -0.060615 | \n",
+ " 5991.195842 | \n",
+ " -0.073439 | \n",
+ " 5815.187326 | \n",
+ " -0.041904 | \n",
+ " 5869.966012 | \n",
+ " -0.051718 | \n",
+ " 5611.310265 | \n",
+ " -0.005375 | \n",
+ " 2193.167972 | \n",
+ " 0.607051 | \n",
+ " 3333.951885 | \n",
+ " 0.402658 | \n",
+ " 4568.961153 | \n",
+ " 0.181382 | \n",
+ " 5193.217918 | \n",
+ " 0.069534 | \n",
+ " 5516.575047 | \n",
+ " 0.011599 | \n",
+ " 5795.097195 | \n",
+ " -0.038304 | \n",
+ " 5708.668205 | \n",
+ " -0.022819 | \n",
+ " 5806.308659 | \n",
+ " -0.040313 | \n",
+ " 5724.849106 | \n",
+ " -0.025718 | \n",
+ " 5763.980812 | \n",
+ " -0.032729 | \n",
+ " 5624.090066 | \n",
+ " -0.007665 | \n",
+ " 9.516454 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 4213.771834 | \n",
+ " 0.311166 | \n",
+ " 4825.940412 | \n",
+ " 0.211094 | \n",
+ " 5681.011294 | \n",
+ " 0.071313 | \n",
+ " 6040.236320 | \n",
+ " 0.012590 | \n",
+ " 6010.251621 | \n",
+ " 0.017492 | \n",
+ " 6040.809248 | \n",
+ " 0.012497 | \n",
+ " 6072.462142 | \n",
+ " 0.007322 | \n",
+ " 6219.755407 | \n",
+ " -0.016756 | \n",
+ " 6225.621623 | \n",
+ " -0.017715 | \n",
+ " 6148.928735 | \n",
+ " -0.005178 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 4317.195582 | \n",
+ " 0.294259 | \n",
+ " 5220.529078 | \n",
+ " 0.146589 | \n",
+ " 6400.227369 | \n",
+ " -0.046258 | \n",
+ " 6949.837827 | \n",
+ " -0.136104 | \n",
+ " 7213.551738 | \n",
+ " -0.179214 | \n",
+ " 7144.965343 | \n",
+ " -0.168002 | \n",
+ " 7042.816321 | \n",
+ " -0.151304 | \n",
+ " 6800.197216 | \n",
+ " -0.111642 | \n",
+ " 6382.959926 | \n",
+ " -0.043436 | \n",
+ " 6120.597362 | \n",
+ " -0.000547 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 4532.535944 | \n",
+ " 0.259057 | \n",
+ " 4782.177425 | \n",
+ " 0.218248 | \n",
+ " 5765.002999 | \n",
+ " 0.057583 | \n",
+ " 6616.765442 | \n",
+ " -0.081656 | \n",
+ " 6540.407431 | \n",
+ " -0.069174 | \n",
+ " 6560.380937 | \n",
+ " -0.072439 | \n",
+ " 6541.498076 | \n",
+ " -0.069352 | \n",
+ " 6445.427868 | \n",
+ " -0.053647 | \n",
+ " 6279.188476 | \n",
+ " -0.026472 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 4204.940450 | \n",
+ " 0.312610 | \n",
+ " 4812.357611 | \n",
+ " 0.213314 | \n",
+ " 5643.187091 | \n",
+ " 0.077497 | \n",
+ " 6067.666325 | \n",
+ " 0.008106 | \n",
+ " 6125.743285 | \n",
+ " -0.001388 | \n",
+ " 6196.138333 | \n",
+ " -0.012895 | \n",
+ " 6238.070629 | \n",
+ " -0.019750 | \n",
+ " 6324.483467 | \n",
+ " -0.033876 | \n",
+ " 6261.602595 | \n",
+ " -0.023597 | \n",
+ " 6120.715936 | \n",
+ " -0.000566 | \n",
+ " 9.552238 | \n",
+ " 6121.822228 | \n",
+ " -0.000747 | \n",
+ " 4565.198469 | \n",
+ " 0.253718 | \n",
+ " 4202.993784 | \n",
+ " 0.312928 | \n",
+ " 3791.454016 | \n",
+ " 0.380203 | \n",
+ " 3482.538323 | \n",
+ " 0.430702 | \n",
+ " 3517.779677 | \n",
+ " 0.424941 | \n",
+ " 3511.064884 | \n",
+ " 0.426039 | \n",
+ " 3523.610302 | \n",
+ " 0.423988 | \n",
+ " 3475.624613 | \n",
+ " 0.431833 | \n",
+ " 3504.931544 | \n",
+ " 0.427042 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 6124.876390 | \n",
+ " -0.001246 | \n",
+ " 4533.065114 | \n",
+ " 0.258971 | \n",
+ " 4036.250074 | \n",
+ " 0.340186 | \n",
+ " 3657.157989 | \n",
+ " 0.402157 | \n",
+ " 3432.644180 | \n",
+ " 0.438859 | \n",
+ " 3416.521741 | \n",
+ " 0.441494 | \n",
+ " 3338.099275 | \n",
+ " 0.454314 | \n",
+ " 3401.714814 | \n",
+ " 0.443915 | \n",
+ " 3414.243011 | \n",
+ " 0.441867 | \n",
+ " 3549.325521 | \n",
+ " 0.419785 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 4630.301104 | \n",
+ " 0.243075 | \n",
+ " 4461.578467 | \n",
+ " 0.270657 | \n",
+ " 4086.940877 | \n",
+ " 0.331899 | \n",
+ " 3867.554025 | \n",
+ " 0.367763 | \n",
+ " 4124.247124 | \n",
+ " 0.325801 | \n",
+ " 4247.664086 | \n",
+ " 0.305626 | \n",
+ " 4175.739512 | \n",
+ " 0.317383 | \n",
+ " 4071.541941 | \n",
+ " 0.334417 | \n",
+ " 4087.077584 | \n",
+ " 0.331877 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 6118.188308 | \n",
+ " -0.000153 | \n",
+ " 4554.336197 | \n",
+ " 0.255493 | \n",
+ " 4087.341630 | \n",
+ " 0.331834 | \n",
+ " 3669.516753 | \n",
+ " 0.400137 | \n",
+ " 3467.364448 | \n",
+ " 0.433183 | \n",
+ " 3470.756627 | \n",
+ " 0.432628 | \n",
+ " 3426.308046 | \n",
+ " 0.439894 | \n",
+ " 3422.427748 | \n",
+ " 0.440529 | \n",
+ " 3367.681185 | \n",
+ " 0.449478 | \n",
+ " 3398.510612 | \n",
+ " 0.444439 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 9.641644 | \n",
+ " 3317.655397 | \n",
+ " 0.470632 | \n",
+ " 4252.098901 | \n",
+ " 0.321531 | \n",
+ " 4965.848450 | \n",
+ " 0.207644 | \n",
+ " 5733.329545 | \n",
+ " 0.085184 | \n",
+ " 6078.686174 | \n",
+ " 0.030079 | \n",
+ " 6173.750086 | \n",
+ " 0.014910 | \n",
+ " 6142.718017 | \n",
+ " 0.019862 | \n",
+ " 6271.061133 | \n",
+ " -0.000617 | \n",
+ " 6362.782912 | \n",
+ " -0.015252 | \n",
+ " 6344.548400 | \n",
+ " -0.012342 | \n",
+ " 6286.679067 | \n",
+ " -0.003109 | \n",
+ " 3332.826395 | \n",
+ " 0.468211 | \n",
+ " 4372.466149 | \n",
+ " 0.302325 | \n",
+ " 5200.909978 | \n",
+ " 0.170138 | \n",
+ " 6249.120862 | \n",
+ " 0.002884 | \n",
+ " 6895.247992 | \n",
+ " -0.100213 | \n",
+ " 7031.352831 | \n",
+ " -0.121930 | \n",
+ " 6866.904602 | \n",
+ " -0.095690 | \n",
+ " 6825.980328 | \n",
+ " -0.089160 | \n",
+ " 6716.099781 | \n",
+ " -0.071627 | \n",
+ " 6500.228772 | \n",
+ " -0.037183 | \n",
+ " 6276.453840 | \n",
+ " -0.001477 | \n",
+ " 4245.435413 | \n",
+ " 0.322594 | \n",
+ " 4744.258516 | \n",
+ " 0.243001 | \n",
+ " 5134.835355 | \n",
+ " 0.180681 | \n",
+ " 5989.696026 | \n",
+ " 0.044278 | \n",
+ " 6600.850248 | \n",
+ " -0.053238 | \n",
+ " 6439.163654 | \n",
+ " -0.027439 | \n",
+ " 6425.883090 | \n",
+ " -0.025320 | \n",
+ " 6511.903490 | \n",
+ " -0.039046 | \n",
+ " 6526.163669 | \n",
+ " -0.041321 | \n",
+ " 6501.302701 | \n",
+ " -0.037354 | \n",
+ " 6267.370049 | \n",
+ " -0.000028 | \n",
+ " 3251.341447 | \n",
+ " 0.481213 | \n",
+ " 4245.552249 | \n",
+ " 0.322576 | \n",
+ " 4889.454447 | \n",
+ " 0.219834 | \n",
+ " 5673.355569 | \n",
+ " 0.094754 | \n",
+ " 6124.177802 | \n",
+ " 0.022820 | \n",
+ " 6225.744929 | \n",
+ " 0.006614 | \n",
+ " 6230.183531 | \n",
+ " 0.005906 | \n",
+ " 6331.818864 | \n",
+ " -0.010311 | \n",
+ " 6421.566444 | \n",
+ " -0.024631 | \n",
+ " 6365.125200 | \n",
+ " -0.015626 | \n",
+ " 6267.614305 | \n",
+ " -0.000067 | \n",
+ " 9.768127 | \n",
+ " 10 | \n",
" NaN | \n",
+ "
\n",
+ " \n",
+ " 66 | \n",
" NaN | \n",
+ " keep_all_rows | \n",
+ " 0 | \n",
+ " 100.0 | \n",
+ " 5.0 | \n",
+ " 0.33 | \n",
+ " 42.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
+ " RF | \n",
+ " TreeSHAP_RF | \n",
+ " 296 | \n",
+ " 146 | \n",
+ " 10 | \n",
+ " 10 | \n",
+ " 3317.655397 | \n",
+ " 0.470632 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
+ " 4 | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
+ " 6 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 3650 | \n",
+ " 0.352780 | \n",
+ " 1438.855135 | \n",
+ " 0.742201 | \n",
+ " 2782.889805 | \n",
+ " 0.501391 | \n",
+ " 4366.241529 | \n",
+ " 0.217703 | \n",
+ " 5070.550880 | \n",
+ " 0.091512 | \n",
+ " 5466.312513 | \n",
+ " 0.020604 | \n",
+ " 5611.598042 | \n",
+ " -0.005427 | \n",
+ " 5618.506871 | \n",
+ " -0.006665 | \n",
+ " 5654.910570 | \n",
+ " -0.013187 | \n",
+ " 5619.409496 | \n",
+ " -0.006826 | \n",
+ " 5634.681385 | \n",
+ " -0.009563 | \n",
+ " 5687.565590 | \n",
+ " -0.019038 | \n",
+ " 2738.215621 | \n",
+ " 0.509396 | \n",
+ " 3923.613699 | \n",
+ " 0.297008 | \n",
+ " 5540.710071 | \n",
+ " 0.007274 | \n",
+ " 6201.689908 | \n",
+ " -0.111153 | \n",
+ " 6467.662659 | \n",
+ " -0.158807 | \n",
+ " 6656.869877 | \n",
+ " -0.192707 | \n",
+ " 6731.266600 | \n",
+ " -0.206037 | \n",
+ " 6580.335137 | \n",
+ " -0.178995 | \n",
+ " 6519.573170 | \n",
+ " -0.168108 | \n",
+ " 6191.864619 | \n",
+ " -0.109393 | \n",
+ " 5589.440875 | \n",
+ " -0.001457 | \n",
+ " 0.097250 | \n",
+ " 0.999983 | \n",
+ " 1548.709747 | \n",
+ " 0.722519 | \n",
+ " 3239.161380 | \n",
+ " 0.419641 | \n",
+ " 4348.167990 | \n",
+ " 0.220941 | \n",
+ " 5168.590233 | \n",
+ " 0.073947 | \n",
+ " 5650.278499 | \n",
+ " -0.012357 | \n",
+ " 6010.622799 | \n",
+ " -0.076920 | \n",
+ " 6015.874192 | \n",
+ " -0.077861 | \n",
+ " 5992.264780 | \n",
+ " -0.073631 | \n",
+ " 5818.049908 | \n",
+ " -0.042417 | \n",
+ " 5611.310265 | \n",
+ " -0.005375 | \n",
+ " 2193.167972 | \n",
+ " 0.607051 | \n",
+ " 3464.273155 | \n",
+ " 0.379308 | \n",
+ " 4770.751640 | \n",
+ " 0.145227 | \n",
+ " 5395.283077 | \n",
+ " 0.033330 | \n",
+ " 5795.554139 | \n",
+ " -0.038386 | \n",
+ " 5967.401983 | \n",
+ " -0.069176 | \n",
+ " 5938.818272 | \n",
+ " -0.064055 | \n",
+ " 5911.916236 | \n",
+ " -0.059235 | \n",
+ " 5826.379101 | \n",
+ " -0.043909 | \n",
+ " 5723.786894 | \n",
+ " -0.025528 | \n",
+ " 5624.090066 | \n",
+ " -0.007665 | \n",
+ " 9.597552 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 4244.202125 | \n",
+ " 0.306192 | \n",
+ " 5180.216168 | \n",
+ " 0.153179 | \n",
+ " 5853.344850 | \n",
+ " 0.043142 | \n",
+ " 6059.064892 | \n",
+ " 0.009512 | \n",
+ " 6033.072523 | \n",
+ " 0.013761 | \n",
+ " 6076.452794 | \n",
+ " 0.006670 | \n",
+ " 6163.188391 | \n",
+ " -0.007509 | \n",
+ " 6167.744088 | \n",
+ " -0.008254 | \n",
+ " 6163.381267 | \n",
+ " -0.007541 | \n",
+ " 6148.928735 | \n",
+ " -0.005178 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 4298.706761 | \n",
+ " 0.297282 | \n",
+ " 5543.796750 | \n",
+ " 0.093744 | \n",
+ " 6597.919515 | \n",
+ " -0.078575 | \n",
+ " 7200.544735 | \n",
+ " -0.177088 | \n",
+ " 7180.863666 | \n",
+ " -0.173870 | \n",
+ " 7178.534520 | \n",
+ " -0.173490 | \n",
+ " 7282.307820 | \n",
+ " -0.190454 | \n",
+ " 7045.106442 | \n",
+ " -0.151678 | \n",
+ " 6518.753085 | \n",
+ " -0.065634 | \n",
+ " 6120.597362 | \n",
+ " -0.000547 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 4539.464977 | \n",
+ " 0.257924 | \n",
+ " 5165.616795 | \n",
+ " 0.155566 | \n",
+ " 5612.968644 | \n",
+ " 0.082437 | \n",
+ " 6545.861568 | \n",
+ " -0.070065 | \n",
+ " 6227.923582 | \n",
+ " -0.018091 | \n",
+ " 6319.939748 | \n",
+ " -0.033133 | \n",
+ " 6328.347984 | \n",
+ " -0.034508 | \n",
+ " 6309.849532 | \n",
+ " -0.031484 | \n",
+ " 6210.926311 | \n",
+ " -0.015313 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 4200.995461 | \n",
+ " 0.313255 | \n",
+ " 5148.796361 | \n",
+ " 0.158316 | \n",
+ " 5749.118505 | \n",
+ " 0.060180 | \n",
+ " 6190.579480 | \n",
+ " -0.011987 | \n",
+ " 6151.965930 | \n",
+ " -0.005674 | \n",
+ " 6235.536408 | \n",
+ " -0.019336 | \n",
+ " 6349.831588 | \n",
+ " -0.038020 | \n",
+ " 6324.912346 | \n",
+ " -0.033946 | \n",
+ " 6213.181953 | \n",
+ " -0.015682 | \n",
+ " 6120.715936 | \n",
+ " -0.000566 | \n",
+ " 9.366884 | \n",
+ " 6121.822228 | \n",
+ " -0.000747 | \n",
+ " 4574.417632 | \n",
+ " 0.252211 | \n",
+ " 3941.660325 | \n",
+ " 0.355649 | \n",
+ " 3882.135957 | \n",
+ " 0.365379 | \n",
+ " 3490.555982 | \n",
+ " 0.429392 | \n",
+ " 3537.260652 | \n",
+ " 0.421757 | \n",
+ " 3553.312832 | \n",
+ " 0.419133 | \n",
+ " 3495.945755 | \n",
+ " 0.428511 | \n",
+ " 3496.831801 | \n",
+ " 0.428366 | \n",
+ " 3529.774799 | \n",
+ " 0.422980 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 6124.876390 | \n",
+ " -0.001246 | \n",
+ " 4525.897079 | \n",
+ " 0.260142 | \n",
+ " 3735.627267 | \n",
+ " 0.389329 | \n",
+ " 3706.773647 | \n",
+ " 0.394046 | \n",
+ " 3391.760003 | \n",
+ " 0.445542 | \n",
+ " 3532.284395 | \n",
+ " 0.422570 | \n",
+ " 3430.875697 | \n",
+ " 0.439148 | \n",
+ " 3452.640648 | \n",
+ " 0.435590 | \n",
+ " 3565.410982 | \n",
+ " 0.417155 | \n",
+ " 3591.843876 | \n",
+ " 0.412834 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 4725.567058 | \n",
+ " 0.227502 | \n",
+ " 3831.850861 | \n",
+ " 0.373600 | \n",
+ " 4110.292001 | \n",
+ " 0.328082 | \n",
+ " 3979.834737 | \n",
+ " 0.349408 | \n",
+ " 4293.630985 | \n",
+ " 0.298111 | \n",
+ " 4481.075995 | \n",
+ " 0.267469 | \n",
+ " 4270.511124 | \n",
+ " 0.301891 | \n",
+ " 4195.289596 | \n",
+ " 0.314187 | \n",
+ " 4229.613224 | \n",
+ " 0.308576 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 6118.188308 | \n",
+ " -0.000153 | \n",
+ " 4570.576428 | \n",
+ " 0.252839 | \n",
+ " 3806.828252 | \n",
+ " 0.377690 | \n",
+ " 3759.608774 | \n",
+ " 0.385409 | \n",
+ " 3408.515859 | \n",
+ " 0.442803 | \n",
+ " 3486.048868 | \n",
+ " 0.430128 | \n",
+ " 3447.239195 | \n",
+ " 0.436473 | \n",
+ " 3399.367759 | \n",
+ " 0.444298 | \n",
+ " 3438.643309 | \n",
+ " 0.437878 | \n",
+ " 3461.606999 | \n",
+ " 0.434124 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 9.647025 | \n",
+ " 3317.655397 | \n",
+ " 0.470632 | \n",
+ " 4151.837191 | \n",
+ " 0.337529 | \n",
+ " 5163.578466 | \n",
+ " 0.176094 | \n",
+ " 5923.044278 | \n",
+ " 0.054913 | \n",
+ " 6195.837162 | \n",
+ " 0.011386 | \n",
+ " 6172.416916 | \n",
+ " 0.015123 | \n",
+ " 6267.709333 | \n",
+ " -0.000082 | \n",
+ " 6357.712212 | \n",
+ " -0.014443 | \n",
+ " 6342.834816 | \n",
+ " -0.012069 | \n",
+ " 6322.005677 | \n",
+ " -0.008745 | \n",
+ " 6286.679067 | \n",
+ " -0.003109 | \n",
+ " 3332.826395 | \n",
+ " 0.468211 | \n",
+ " 4252.332749 | \n",
+ " 0.321494 | \n",
+ " 5500.769377 | \n",
+ " 0.122292 | \n",
+ " 6499.331943 | \n",
+ " -0.037040 | \n",
+ " 7017.833958 | \n",
+ " -0.119772 | \n",
+ " 6999.075380 | \n",
+ " -0.116779 | \n",
+ " 7064.166452 | \n",
+ " -0.127165 | \n",
+ " 7161.699581 | \n",
+ " -0.142728 | \n",
+ " 7016.127259 | \n",
+ " -0.119500 | \n",
+ " 6654.176147 | \n",
+ " -0.061747 | \n",
+ " 6276.453840 | \n",
+ " -0.001477 | \n",
+ " 4245.435413 | \n",
+ " 0.322594 | \n",
+ " 4651.418299 | \n",
+ " 0.257815 | \n",
+ " 5434.706040 | \n",
+ " 0.132833 | \n",
+ " 5996.028512 | \n",
+ " 0.043268 | \n",
+ " 6553.462829 | \n",
+ " -0.045677 | \n",
+ " 6346.476672 | \n",
+ " -0.012650 | \n",
+ " 6452.011697 | \n",
+ " -0.029489 | \n",
+ " 6466.410333 | \n",
+ " -0.031787 | \n",
+ " 6456.925559 | \n",
+ " -0.030273 | \n",
+ " 6384.095136 | \n",
+ " -0.018652 | \n",
+ " 6267.370049 | \n",
+ " -0.000028 | \n",
+ " 3251.341447 | \n",
+ " 0.481213 | \n",
+ " 4151.615634 | \n",
+ " 0.337564 | \n",
+ " 5150.085657 | \n",
+ " 0.178247 | \n",
+ " 5841.931213 | \n",
+ " 0.067856 | \n",
+ " 6257.791966 | \n",
+ " 0.001501 | \n",
+ " 6220.642475 | \n",
+ " 0.007428 | \n",
+ " 6374.114987 | \n",
+ " -0.017060 | \n",
+ " 6474.285866 | \n",
+ " -0.033043 | \n",
+ " 6449.857168 | \n",
+ " -0.029146 | \n",
+ " 6360.266687 | \n",
+ " -0.014850 | \n",
+ " 6267.614305 | \n",
+ " -0.000067 | \n",
+ " 9.973668 | \n",
+ " 10 | \n",
" NaN | \n",
+ "
\n",
+ " \n",
+ " 67 | \n",
" NaN | \n",
+ " keep_all_rows | \n",
+ " 0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -2247,6 +5333,483 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
+ " RF_plus | \n",
+ " Kernel_SHAP_RF_plus | \n",
+ " 296 | \n",
+ " 146 | \n",
+ " 10 | \n",
+ " 10 | \n",
+ " 3251.341447 | \n",
+ " 0.481213 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
+ " 4 | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
+ " 6 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 8563 | \n",
+ " 151.621587 | \n",
+ " 1438.855135 | \n",
+ " 0.742201 | \n",
+ " 2749.901178 | \n",
+ " 0.507302 | \n",
+ " 4346.155760 | \n",
+ " 0.221302 | \n",
+ " 5105.225598 | \n",
+ " 0.085300 | \n",
+ " 5126.939895 | \n",
+ " 0.081409 | \n",
+ " 5288.691321 | \n",
+ " 0.052428 | \n",
+ " 5392.616386 | \n",
+ " 0.033808 | \n",
+ " 5490.010870 | \n",
+ " 0.016358 | \n",
+ " 5642.366051 | \n",
+ " -0.010939 | \n",
+ " 5642.172216 | \n",
+ " -0.010905 | \n",
+ " 5687.565590 | \n",
+ " -0.019038 | \n",
+ " 2738.215621 | \n",
+ " 0.509396 | \n",
+ " 3659.801644 | \n",
+ " 0.344275 | \n",
+ " 5496.490785 | \n",
+ " 0.015197 | \n",
+ " 5950.452784 | \n",
+ " -0.066139 | \n",
+ " 6108.604691 | \n",
+ " -0.094475 | \n",
+ " 6296.639581 | \n",
+ " -0.128165 | \n",
+ " 6046.285075 | \n",
+ " -0.083309 | \n",
+ " 5975.717171 | \n",
+ " -0.070666 | \n",
+ " 5749.590114 | \n",
+ " -0.030151 | \n",
+ " 5741.037438 | \n",
+ " -0.028618 | \n",
+ " 5589.440875 | \n",
+ " -0.001457 | \n",
+ " 0.097250 | \n",
+ " 0.999983 | \n",
+ " 1377.246667 | \n",
+ " 0.753240 | \n",
+ " 3380.234480 | \n",
+ " 0.394365 | \n",
+ " 4584.976546 | \n",
+ " 0.178512 | \n",
+ " 5219.394868 | \n",
+ " 0.064844 | \n",
+ " 5552.852007 | \n",
+ " 0.005099 | \n",
+ " 5657.061402 | \n",
+ " -0.013572 | \n",
+ " 5778.266563 | \n",
+ " -0.035289 | \n",
+ " 5632.206444 | \n",
+ " -0.009119 | \n",
+ " 5673.012560 | \n",
+ " -0.016430 | \n",
+ " 5611.310265 | \n",
+ " -0.005375 | \n",
+ " 2193.167972 | \n",
+ " 0.607051 | \n",
+ " 3313.295136 | \n",
+ " 0.406359 | \n",
+ " 4771.879930 | \n",
+ " 0.145025 | \n",
+ " 5267.557812 | \n",
+ " 0.056215 | \n",
+ " 5407.976223 | \n",
+ " 0.031056 | \n",
+ " 5588.330353 | \n",
+ " -0.001258 | \n",
+ " 5597.096985 | \n",
+ " -0.002829 | \n",
+ " 5599.602808 | \n",
+ " -0.003278 | \n",
+ " 5660.876322 | \n",
+ " -0.014256 | \n",
+ " 5635.083783 | \n",
+ " -0.009635 | \n",
+ " 5624.090066 | \n",
+ " -0.007665 | \n",
+ " 9.634410 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 4405.069590 | \n",
+ " 0.279894 | \n",
+ " 5324.958907 | \n",
+ " 0.129518 | \n",
+ " 5969.752485 | \n",
+ " 0.024112 | \n",
+ " 6107.021507 | \n",
+ " 0.001673 | \n",
+ " 6094.252440 | \n",
+ " 0.003760 | \n",
+ " 6125.304668 | \n",
+ " -0.001316 | \n",
+ " 6099.205558 | \n",
+ " 0.002950 | \n",
+ " 6128.170963 | \n",
+ " -0.001785 | \n",
+ " 6156.521984 | \n",
+ " -0.006419 | \n",
+ " 6148.928735 | \n",
+ " -0.005178 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 4666.607280 | \n",
+ " 0.237140 | \n",
+ " 5609.077406 | \n",
+ " 0.083073 | \n",
+ " 6687.347282 | \n",
+ " -0.093194 | \n",
+ " 7219.572194 | \n",
+ " -0.180198 | \n",
+ " 7191.487748 | \n",
+ " -0.175607 | \n",
+ " 7079.444666 | \n",
+ " -0.157291 | \n",
+ " 6516.825963 | \n",
+ " -0.065319 | \n",
+ " 6264.367986 | \n",
+ " -0.024049 | \n",
+ " 6157.597738 | \n",
+ " -0.006595 | \n",
+ " 6120.597362 | \n",
+ " -0.000547 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 4889.411544 | \n",
+ " 0.200718 | \n",
+ " 5347.951315 | \n",
+ " 0.125759 | \n",
+ " 5936.846928 | \n",
+ " 0.029491 | \n",
+ " 6838.552159 | \n",
+ " -0.117912 | \n",
+ " 6813.001549 | \n",
+ " -0.113735 | \n",
+ " 6800.556926 | \n",
+ " -0.111701 | \n",
+ " 6317.283208 | \n",
+ " -0.032699 | \n",
+ " 6103.421818 | \n",
+ " 0.002261 | \n",
+ " 6183.841461 | \n",
+ " -0.010885 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 4407.621208 | \n",
+ " 0.279477 | \n",
+ " 5176.857967 | \n",
+ " 0.153728 | \n",
+ " 5889.167837 | \n",
+ " 0.037286 | \n",
+ " 6159.425021 | \n",
+ " -0.006894 | \n",
+ " 6183.331053 | \n",
+ " -0.010802 | \n",
+ " 6178.665567 | \n",
+ " -0.010039 | \n",
+ " 6132.201088 | \n",
+ " -0.002443 | \n",
+ " 6152.552330 | \n",
+ " -0.005770 | \n",
+ " 6137.879384 | \n",
+ " -0.003372 | \n",
+ " 6120.715936 | \n",
+ " -0.000566 | \n",
+ " 9.595195 | \n",
+ " 6121.822228 | \n",
+ " -0.000747 | \n",
+ " 4277.329012 | \n",
+ " 0.300776 | \n",
+ " 3914.729195 | \n",
+ " 0.360051 | \n",
+ " 3751.300613 | \n",
+ " 0.386767 | \n",
+ " 3529.894033 | \n",
+ " 0.422961 | \n",
+ " 3488.042689 | \n",
+ " 0.429803 | \n",
+ " 3548.661541 | \n",
+ " 0.419893 | \n",
+ " 3601.120556 | \n",
+ " 0.411317 | \n",
+ " 3560.828284 | \n",
+ " 0.417904 | \n",
+ " 3545.626442 | \n",
+ " 0.420389 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 6124.876390 | \n",
+ " -0.001246 | \n",
+ " 4181.487573 | \n",
+ " 0.316444 | \n",
+ " 3802.852124 | \n",
+ " 0.378340 | \n",
+ " 3592.998939 | \n",
+ " 0.412645 | \n",
+ " 3269.047589 | \n",
+ " 0.465602 | \n",
+ " 3400.390530 | \n",
+ " 0.444131 | \n",
+ " 3462.299783 | \n",
+ " 0.434011 | \n",
+ " 3561.227406 | \n",
+ " 0.417839 | \n",
+ " 3545.027373 | \n",
+ " 0.420487 | \n",
+ " 3560.528646 | \n",
+ " 0.417953 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 4273.624084 | \n",
+ " 0.301382 | \n",
+ " 4303.050144 | \n",
+ " 0.296572 | \n",
+ " 3672.449170 | \n",
+ " 0.399657 | \n",
+ " 3776.282103 | \n",
+ " 0.382683 | \n",
+ " 4002.617602 | \n",
+ " 0.345684 | \n",
+ " 4119.722671 | \n",
+ " 0.326541 | \n",
+ " 4339.266432 | \n",
+ " 0.290651 | \n",
+ " 4422.473066 | \n",
+ " 0.277049 | \n",
+ " 4409.495930 | \n",
+ " 0.279171 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 6118.188308 | \n",
+ " -0.000153 | \n",
+ " 4312.856796 | \n",
+ " 0.294968 | \n",
+ " 3869.397091 | \n",
+ " 0.367462 | \n",
+ " 3620.284900 | \n",
+ " 0.408185 | \n",
+ " 3385.419843 | \n",
+ " 0.446578 | \n",
+ " 3373.235561 | \n",
+ " 0.448570 | \n",
+ " 3434.690834 | \n",
+ " 0.438524 | \n",
+ " 3497.877026 | \n",
+ " 0.428195 | \n",
+ " 3478.243780 | \n",
+ " 0.431404 | \n",
+ " 3488.432591 | \n",
+ " 0.429739 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 10.038960 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -2329,234 +5892,21 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
- " 4690 | \n",
- " 2.550201 | \n",
- " 1599.333649 | \n",
- " 0.737912 | \n",
- " 3139.907366 | \n",
- " 0.485454 | \n",
- " 4304.751910 | \n",
- " 0.294568 | \n",
- " 5189.976398 | \n",
- " 0.149503 | \n",
- " 5808.092449 | \n",
- " 0.048211 | \n",
- " 5979.670912 | \n",
- " 0.020094 | \n",
- " 6126.709725 | \n",
- " -0.004002 | \n",
- " 6162.581437 | \n",
- " -0.009881 | \n",
- " 6100.482692 | \n",
- " 0.000296 | \n",
- " 6098.125073 | \n",
- " 0.000682 | \n",
- " 6136.821625 | \n",
- " -0.005659 | \n",
- " 2821.915630 | \n",
- " 0.537564 | \n",
- " 4107.855143 | \n",
- " 0.326834 | \n",
- " 5559.862756 | \n",
- " 0.088889 | \n",
- " 6349.285129 | \n",
- " -0.040476 | \n",
- " 6869.438005 | \n",
- " -0.125715 | \n",
- " 7111.388743 | \n",
- " -0.165364 | \n",
- " 7315.462544 | \n",
- " -0.198807 | \n",
- " 7313.503384 | \n",
- " -0.198486 | \n",
- " 7088.936649 | \n",
- " -0.161685 | \n",
- " 6596.083346 | \n",
- " -0.080920 | \n",
- " 6102.287573 | \n",
- " 0.0 | \n",
- " 0.760518 | \n",
- " 0.999875 | \n",
- " 1763.906154 | \n",
- " 0.710943 | \n",
- " 3323.255445 | \n",
- " 0.455408 | \n",
- " 4813.473905 | \n",
- " 0.211202 | \n",
- " 5344.880717 | \n",
- " 0.124119 | \n",
- " 5630.315250 | \n",
- " 0.077344 | \n",
- " 5884.420100 | \n",
- " 0.035703 | \n",
- " 6344.961992 | \n",
- " -0.039768 | \n",
- " 6600.780924 | \n",
- " -0.081690 | \n",
- " 6766.067981 | \n",
- " -0.108776 | \n",
- " 7157.760530 | \n",
- " -0.172963 | \n",
- " 2334.402428 | \n",
- " 0.617455 | \n",
- " 3727.738049 | \n",
- " 0.389124 | \n",
- " 4792.390428 | \n",
- " 0.214657 | \n",
- " 5403.449429 | \n",
- " 0.114521 | \n",
- " 5987.595488 | \n",
- " 0.018795 | \n",
- " 6134.983178 | \n",
- " -0.005358 | \n",
- " 6293.557154 | \n",
- " -0.031344 | \n",
- " 6305.937749 | \n",
- " -0.033373 | \n",
- " 6243.400250 | \n",
- " -0.023125 | \n",
- " 6177.260466 | \n",
- " -0.012286 | \n",
- " 6131.312645 | \n",
- " -0.004756 | \n",
- " 10.852957 | \n",
- " 3072.457734 | \n",
- " 0.448450 | \n",
- " 3599.197638 | \n",
- " 0.353892 | \n",
- " 4064.045641 | \n",
- " 0.270445 | \n",
- " 4786.645423 | \n",
- " 0.140728 | \n",
- " 5216.701738 | \n",
- " 0.063527 | \n",
- " 5425.473666 | \n",
- " 0.026049 | \n",
- " 5590.326152 | \n",
- " -0.003544 | \n",
- " 5562.124282 | \n",
- " 0.001518 | \n",
- " 5644.709360 | \n",
- " -0.013307 | \n",
- " 5619.576540 | \n",
- " -0.008795 | \n",
- " 5664.609603 | \n",
- " -0.016879 | \n",
- " 3213.858553 | \n",
- " 0.423066 | \n",
- " 4037.406723 | \n",
- " 0.275227 | \n",
- " 5200.381743 | \n",
- " 0.066456 | \n",
- " 5884.153057 | \n",
- " -0.056290 | \n",
- " 6556.102398 | \n",
- " -0.176915 | \n",
- " 6885.746921 | \n",
- " -0.236091 | \n",
- " 6917.122114 | \n",
- " -0.241723 | \n",
- " 6905.819125 | \n",
- " -0.239694 | \n",
- " 6489.716483 | \n",
- " -0.164998 | \n",
- " 5999.861947 | \n",
- " -0.077062 | \n",
- " 5585.176699 | \n",
- " -0.002620 | \n",
- " 3725.748845 | \n",
- " 0.331174 | \n",
- " 4237.968847 | \n",
- " 0.239223 | \n",
- " 5811.342427 | \n",
- " -0.043220 | \n",
- " 7035.886520 | \n",
- " -0.263043 | \n",
- " 6466.436133 | \n",
- " -0.160819 | \n",
- " 6318.690304 | \n",
- " -0.134296 | \n",
- " 6248.073414 | \n",
- " -0.121619 | \n",
- " 6390.760993 | \n",
- " -0.147234 | \n",
- " 6417.178461 | \n",
- " -0.151976 | \n",
- " 6340.479231 | \n",
- " -0.138207 | \n",
- " 6392.430662 | \n",
- " -0.147533 | \n",
- " 3043.279335 | \n",
- " 0.453687 | \n",
- " 3747.546011 | \n",
- " 0.327261 | \n",
- " 4388.732777 | \n",
- " 0.212159 | \n",
- " 5042.162467 | \n",
- " 0.094859 | \n",
- " 5459.350264 | \n",
- " 0.019968 | \n",
- " 5555.680287 | \n",
- " 0.002675 | \n",
- " 5702.488350 | \n",
- " -0.023679 | \n",
- " 5680.464377 | \n",
- " -0.019725 | \n",
- " 5695.898765 | \n",
- " -0.022496 | \n",
- " 5664.517560 | \n",
- " -0.016863 | \n",
- " 5655.363927 | \n",
- " -0.015219 | \n",
- " 7.412112 | \n",
- " 6 | \n",
" NaN | \n",
- "
\n",
- " \n",
- " 66 | \n",
" NaN | \n",
- " keep_all_rows | \n",
- " 0 | \n",
- " 100.0 | \n",
- " 5.0 | \n",
- " 0.33 | \n",
- " 42.0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
- " RF | \n",
- " TreeSHAP_RF | \n",
- " 296 | \n",
- " 146 | \n",
" 10 | \n",
- " 6 | \n",
- " 3072.457734 | \n",
- " 0.448450 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
+ " RandomForestRegressor(max_features=0.33, min_s... | \n",
+ "
\n",
+ " \n",
+ " 68 | \n",
" NaN | \n",
+ " keep_all_rows | \n",
+ " 0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -2566,7 +5916,580 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
+ " RF_plus | \n",
+ " LFI_with_raw_RF_plus | \n",
+ " 296 | \n",
+ " 146 | \n",
+ " 10 | \n",
+ " 10 | \n",
+ " 3251.341447 | \n",
+ " 0.481213 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
+ " 4 | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
+ " 6 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 8563 | \n",
+ " 2.607143 | \n",
+ " 1438.855135 | \n",
+ " 0.742201 | \n",
+ " 2572.532707 | \n",
+ " 0.539081 | \n",
+ " 4175.221232 | \n",
+ " 0.251928 | \n",
+ " 4881.927373 | \n",
+ " 0.125308 | \n",
+ " 5173.172791 | \n",
+ " 0.073126 | \n",
+ " 5217.655724 | \n",
+ " 0.065156 | \n",
+ " 5405.903732 | \n",
+ " 0.031427 | \n",
+ " 5481.723324 | \n",
+ " 0.017843 | \n",
+ " 5538.033353 | \n",
+ " 0.007754 | \n",
+ " 5649.927048 | \n",
+ " -0.012294 | \n",
+ " 5687.565590 | \n",
+ " -0.019038 | \n",
+ " 2738.215621 | \n",
+ " 0.509396 | \n",
+ " 3827.975616 | \n",
+ " 0.314144 | \n",
+ " 5456.335042 | \n",
+ " 0.022392 | \n",
+ " 6101.608395 | \n",
+ " -0.093222 | \n",
+ " 6497.883717 | \n",
+ " -0.164222 | \n",
+ " 6312.108631 | \n",
+ " -0.130937 | \n",
+ " 6522.814156 | \n",
+ " -0.168689 | \n",
+ " 6243.676990 | \n",
+ " -0.118676 | \n",
+ " 6056.418996 | \n",
+ " -0.085125 | \n",
+ " 5886.908055 | \n",
+ " -0.054754 | \n",
+ " 5589.440875 | \n",
+ " -0.001457 | \n",
+ " 0.097250 | \n",
+ " 0.999983 | \n",
+ " 1401.369064 | \n",
+ " 0.748918 | \n",
+ " 3294.968987 | \n",
+ " 0.409642 | \n",
+ " 4350.842152 | \n",
+ " 0.220462 | \n",
+ " 5097.939455 | \n",
+ " 0.086605 | \n",
+ " 5404.702722 | \n",
+ " 0.031643 | \n",
+ " 5415.757183 | \n",
+ " 0.029662 | \n",
+ " 5649.120636 | \n",
+ " -0.012150 | \n",
+ " 5755.516127 | \n",
+ " -0.031212 | \n",
+ " 5785.642537 | \n",
+ " -0.036610 | \n",
+ " 5611.310265 | \n",
+ " -0.005375 | \n",
+ " 2193.167972 | \n",
+ " 0.607051 | \n",
+ " 3289.911059 | \n",
+ " 0.410549 | \n",
+ " 4688.223178 | \n",
+ " 0.160014 | \n",
+ " 5262.297817 | \n",
+ " 0.057157 | \n",
+ " 5572.520393 | \n",
+ " 0.001575 | \n",
+ " 5626.114993 | \n",
+ " -0.008028 | \n",
+ " 5720.182130 | \n",
+ " -0.024882 | \n",
+ " 5708.412501 | \n",
+ " -0.022773 | \n",
+ " 5673.183423 | \n",
+ " -0.016461 | \n",
+ " 5664.500329 | \n",
+ " -0.014905 | \n",
+ " 5624.090066 | \n",
+ " -0.007665 | \n",
+ " 9.592882 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 4364.788724 | \n",
+ " 0.286479 | \n",
+ " 5096.309073 | \n",
+ " 0.166896 | \n",
+ " 5689.664778 | \n",
+ " 0.069899 | \n",
+ " 6158.371502 | \n",
+ " -0.006722 | \n",
+ " 6203.838469 | \n",
+ " -0.014154 | \n",
+ " 6310.867104 | \n",
+ " -0.031650 | \n",
+ " 6234.113582 | \n",
+ " -0.019103 | \n",
+ " 6146.976283 | \n",
+ " -0.004859 | \n",
+ " 6087.385960 | \n",
+ " 0.004883 | \n",
+ " 6148.928735 | \n",
+ " -0.005178 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 4665.190648 | \n",
+ " 0.237372 | \n",
+ " 5658.394843 | \n",
+ " 0.075011 | \n",
+ " 6659.387508 | \n",
+ " -0.088624 | \n",
+ " 7340.405511 | \n",
+ " -0.199951 | \n",
+ " 7230.734184 | \n",
+ " -0.182023 | \n",
+ " 7129.372180 | \n",
+ " -0.165453 | \n",
+ " 6842.169559 | \n",
+ " -0.118503 | \n",
+ " 6660.330947 | \n",
+ " -0.088778 | \n",
+ " 6404.891031 | \n",
+ " -0.047021 | \n",
+ " 6120.597362 | \n",
+ " -0.000547 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 4832.984280 | \n",
+ " 0.209942 | \n",
+ " 5039.114767 | \n",
+ " 0.176246 | \n",
+ " 5945.292532 | \n",
+ " 0.028111 | \n",
+ " 7070.221311 | \n",
+ " -0.155784 | \n",
+ " 7064.584402 | \n",
+ " -0.154862 | \n",
+ " 6776.496533 | \n",
+ " -0.107768 | \n",
+ " 6499.619097 | \n",
+ " -0.062506 | \n",
+ " 6431.116718 | \n",
+ " -0.051308 | \n",
+ " 6231.886900 | \n",
+ " -0.018739 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 4375.022227 | \n",
+ " 0.284806 | \n",
+ " 5125.537268 | \n",
+ " 0.162118 | \n",
+ " 5746.818059 | \n",
+ " 0.060556 | \n",
+ " 6268.233739 | \n",
+ " -0.024681 | \n",
+ " 6296.207000 | \n",
+ " -0.029254 | \n",
+ " 6385.842720 | \n",
+ " -0.043907 | \n",
+ " 6292.629363 | \n",
+ " -0.028669 | \n",
+ " 6221.064362 | \n",
+ " -0.016970 | \n",
+ " 6135.388651 | \n",
+ " -0.002965 | \n",
+ " 6120.715936 | \n",
+ " -0.000566 | \n",
+ " 9.291578 | \n",
+ " 6121.822228 | \n",
+ " -0.000747 | \n",
+ " 4323.754030 | \n",
+ " 0.293187 | \n",
+ " 4059.848931 | \n",
+ " 0.336328 | \n",
+ " 3856.213349 | \n",
+ " 0.369617 | \n",
+ " 3459.946577 | \n",
+ " 0.434395 | \n",
+ " 3542.798313 | \n",
+ " 0.420852 | \n",
+ " 3499.935693 | \n",
+ " 0.427858 | \n",
+ " 3587.957177 | \n",
+ " 0.413469 | \n",
+ " 3584.258787 | \n",
+ " 0.414074 | \n",
+ " 3516.033741 | \n",
+ " 0.425227 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 6124.876390 | \n",
+ " -0.001246 | \n",
+ " 4178.413687 | \n",
+ " 0.316946 | \n",
+ " 3780.783134 | \n",
+ " 0.381948 | \n",
+ " 3531.958353 | \n",
+ " 0.422624 | \n",
+ " 3439.178531 | \n",
+ " 0.437790 | \n",
+ " 3468.716167 | \n",
+ " 0.432962 | \n",
+ " 3543.240528 | \n",
+ " 0.420779 | \n",
+ " 3573.537624 | \n",
+ " 0.415826 | \n",
+ " 3493.357573 | \n",
+ " 0.428934 | \n",
+ " 3446.529715 | \n",
+ " 0.436589 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 4444.060554 | \n",
+ " 0.273520 | \n",
+ " 4504.391659 | \n",
+ " 0.263658 | \n",
+ " 3900.837880 | \n",
+ " 0.362322 | \n",
+ " 3990.586257 | \n",
+ " 0.347651 | \n",
+ " 4186.632856 | \n",
+ " 0.315603 | \n",
+ " 4288.927715 | \n",
+ " 0.298880 | \n",
+ " 4495.201911 | \n",
+ " 0.265160 | \n",
+ " 4377.737177 | \n",
+ " 0.284362 | \n",
+ " 4291.562443 | \n",
+ " 0.298450 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 6118.188308 | \n",
+ " -0.000153 | \n",
+ " 4347.438699 | \n",
+ " 0.289315 | \n",
+ " 3913.814050 | \n",
+ " 0.360201 | \n",
+ " 3635.666334 | \n",
+ " 0.405670 | \n",
+ " 3362.368505 | \n",
+ " 0.450347 | \n",
+ " 3401.274428 | \n",
+ " 0.443987 | \n",
+ " 3406.397571 | \n",
+ " 0.443149 | \n",
+ " 3497.782692 | \n",
+ " 0.428210 | \n",
+ " 3490.790081 | \n",
+ " 0.429353 | \n",
+ " 3473.687224 | \n",
+ " 0.432149 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 9.786609 | \n",
+ " 3317.655397 | \n",
+ " 0.470632 | \n",
+ " 4147.385047 | \n",
+ " 0.338239 | \n",
+ " 4987.539777 | \n",
+ " 0.204183 | \n",
+ " 5932.927451 | \n",
+ " 0.053336 | \n",
+ " 6292.487953 | \n",
+ " -0.004036 | \n",
+ " 6302.699742 | \n",
+ " -0.005665 | \n",
+ " 6448.386612 | \n",
+ " -0.028911 | \n",
+ " 6412.611071 | \n",
+ " -0.023203 | \n",
+ " 6337.685910 | \n",
+ " -0.011247 | \n",
+ " 6278.027761 | \n",
+ " -0.001728 | \n",
+ " 6286.679067 | \n",
+ " -0.003109 | \n",
+ " 3332.826395 | \n",
+ " 0.468211 | \n",
+ " 4359.423484 | \n",
+ " 0.304406 | \n",
+ " 5585.910286 | \n",
+ " 0.108707 | \n",
+ " 6615.984755 | \n",
+ " -0.055653 | \n",
+ " 7217.577286 | \n",
+ " -0.151644 | \n",
+ " 7214.779536 | \n",
+ " -0.151197 | \n",
+ " 7129.172211 | \n",
+ " -0.137538 | \n",
+ " 6905.484625 | \n",
+ " -0.101846 | \n",
+ " 6732.551850 | \n",
+ " -0.074253 | \n",
+ " 6519.281447 | \n",
+ " -0.040223 | \n",
+ " 6276.453840 | \n",
+ " -0.001477 | \n",
+ " 4245.435413 | \n",
+ " 0.322594 | \n",
+ " 4453.127851 | \n",
+ " 0.289455 | \n",
+ " 5212.469751 | \n",
+ " 0.168293 | \n",
+ " 6288.165970 | \n",
+ " -0.003346 | \n",
+ " 6851.244552 | \n",
+ " -0.093191 | \n",
+ " 6812.276313 | \n",
+ " -0.086974 | \n",
+ " 6928.881119 | \n",
+ " -0.105579 | \n",
+ " 6522.271203 | \n",
+ " -0.040700 | \n",
+ " 6489.344892 | \n",
+ " -0.035446 | \n",
+ " 6399.173120 | \n",
+ " -0.021058 | \n",
+ " 6267.370049 | \n",
+ " -0.000028 | \n",
+ " 3251.341447 | \n",
+ " 0.481213 | \n",
+ " 4185.950870 | \n",
+ " 0.332086 | \n",
+ " 5088.527932 | \n",
+ " 0.188069 | \n",
+ " 5921.367059 | \n",
+ " 0.055181 | \n",
+ " 6385.221264 | \n",
+ " -0.018832 | \n",
+ " 6420.552407 | \n",
+ " -0.024470 | \n",
+ " 6519.528273 | \n",
+ " -0.040262 | \n",
+ " 6451.424694 | \n",
+ " -0.029396 | \n",
+ " 6391.825749 | \n",
+ " -0.019886 | \n",
+ " 6293.769573 | \n",
+ " -0.004240 | \n",
+ " 6267.614305 | \n",
+ " -0.000067 | \n",
+ " 9.742957 | \n",
+ " 10 | \n",
+ " RandomForestRegressor(max_features=0.33, min_s... | \n",
+ "
\n",
+ " \n",
+ " 69 | \n",
" NaN | \n",
+ " keep_all_rows | \n",
+ " 0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -2576,6 +6499,483 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
+ " RF_plus | \n",
+ " LIME_RF_plus | \n",
+ " 296 | \n",
+ " 146 | \n",
+ " 10 | \n",
+ " 10 | \n",
+ " 3251.341447 | \n",
+ " 0.481213 | \n",
+ " 274 | \n",
+ " 69 | \n",
+ " 155 | \n",
+ " 30 | \n",
+ " 84 | \n",
+ " 39 | \n",
+ " 82 | \n",
+ " 2 | \n",
+ " 261 | \n",
+ " 124 | \n",
+ " 9 | \n",
+ " 10 | \n",
+ " 42 | \n",
+ " 68 | \n",
+ " 277 | \n",
+ " 51 | \n",
+ " 282 | \n",
+ " 71 | \n",
+ " 92 | \n",
+ " 77 | \n",
+ " 148 | \n",
+ " 102 | \n",
+ " 211 | \n",
+ " 80 | \n",
+ " 60 | \n",
+ " 76 | \n",
+ " 218 | \n",
+ " 142 | \n",
+ " 262 | \n",
+ " 127 | \n",
+ " 46 | \n",
+ " 95 | \n",
+ " 45 | \n",
+ " 70 | \n",
+ " 236 | \n",
+ " 93 | \n",
+ " 228 | \n",
+ " 67 | \n",
+ " 132 | \n",
+ " 0 | \n",
+ " 143 | \n",
+ " 105 | \n",
+ " 167 | \n",
+ " 82 | \n",
+ " 152 | \n",
+ " 136 | \n",
+ " 93 | \n",
+ " 40 | \n",
+ " 113 | \n",
+ " 54 | \n",
+ " 5 | \n",
+ " 28 | \n",
+ " 238 | \n",
+ " 74 | \n",
+ " 251 | \n",
+ " 119 | \n",
+ " 170 | \n",
+ " 18 | \n",
+ " 186 | \n",
+ " 9 | \n",
+ " 193 | \n",
+ " 58 | \n",
+ " 33 | \n",
+ " 99 | \n",
+ " 222 | \n",
+ " 73 | \n",
+ " 216 | \n",
+ " 97 | \n",
+ " 197 | \n",
+ " 128 | \n",
+ " 73 | \n",
+ " 122 | \n",
+ " 182 | \n",
+ " 55 | \n",
+ " 119 | \n",
+ " 90 | \n",
+ " 285 | \n",
+ " 129 | \n",
+ " 202 | \n",
+ " 79 | \n",
+ " 204 | \n",
+ " 4 | \n",
+ " 179 | \n",
+ " 87 | \n",
+ " 177 | \n",
+ " 83 | \n",
+ " 111 | \n",
+ " 115 | \n",
+ " 59 | \n",
+ " 81 | \n",
+ " 226 | \n",
+ " 72 | \n",
+ " 25 | \n",
+ " 144 | \n",
+ " 77 | \n",
+ " 78 | \n",
+ " 6 | \n",
+ " 126 | \n",
+ " 175 | \n",
+ " 132 | \n",
+ " 164 | \n",
+ " 106 | \n",
+ " 140 | \n",
+ " 75 | \n",
+ " 30 | \n",
+ " 61 | \n",
+ " 22 | \n",
+ " 143 | \n",
+ " 245 | \n",
+ " 131 | \n",
+ " 24 | \n",
+ " 123 | \n",
+ " 56 | \n",
+ " 89 | \n",
+ " 144 | \n",
+ " 33 | \n",
+ " 124 | \n",
+ " 133 | \n",
+ " 97 | \n",
+ " 14 | \n",
+ " 63 | \n",
+ " 88 | \n",
+ " 17 | \n",
+ " 140 | \n",
+ " 215 | \n",
+ " 11 | \n",
+ " 219 | \n",
+ " 13 | \n",
+ " 183 | \n",
+ " 15 | \n",
+ " 114 | \n",
+ " 139 | \n",
+ " 76 | \n",
+ " 64 | \n",
+ " 284 | \n",
+ " 19 | \n",
+ " 66 | \n",
+ " 44 | \n",
+ " 178 | \n",
+ " 35 | \n",
+ " 154 | \n",
+ " 56 | \n",
+ " 75 | \n",
+ " 6 | \n",
+ " 19 | \n",
+ " 107 | \n",
+ " 108 | \n",
+ " 12 | \n",
+ " 79 | \n",
+ " 113 | \n",
+ " 118 | \n",
+ " 141 | \n",
+ " 72 | \n",
+ " 49 | \n",
+ " 15 | \n",
+ " 25 | \n",
+ " 10 | \n",
+ " 41 | \n",
+ " 101 | \n",
+ " 38 | \n",
+ " 68 | \n",
+ " 130 | \n",
+ " 125 | \n",
+ " 42 | \n",
+ " 37 | \n",
+ " 8 | \n",
+ " 16 | \n",
+ " 101 | \n",
+ " 293 | \n",
+ " 125 | \n",
+ " 139 | \n",
+ " 1 | \n",
+ " 266 | \n",
+ " 137 | \n",
+ " 67 | \n",
+ " 65 | \n",
+ " 90 | \n",
+ " 22 | \n",
+ " 69 | \n",
+ " 85 | \n",
+ " 288 | \n",
+ " 46 | \n",
+ " 165 | \n",
+ " 103 | \n",
+ " 126 | \n",
+ " 145 | \n",
+ " 221 | \n",
+ " 111 | \n",
+ " 173 | \n",
+ " 100 | \n",
+ " 18 | \n",
+ " 57 | \n",
+ " 172 | \n",
+ " 53 | \n",
+ " 96 | \n",
+ " 109 | \n",
+ " 146 | \n",
+ " 24 | \n",
+ " 86 | \n",
+ " 17 | \n",
+ " 8563 | \n",
+ " 315.562780 | \n",
+ " 1438.855135 | \n",
+ " 0.742201 | \n",
+ " 2720.135924 | \n",
+ " 0.512635 | \n",
+ " 3782.575791 | \n",
+ " 0.322278 | \n",
+ " 4604.837368 | \n",
+ " 0.174954 | \n",
+ " 5200.792476 | \n",
+ " 0.068177 | \n",
+ " 5225.942001 | \n",
+ " 0.063671 | \n",
+ " 5344.152735 | \n",
+ " 0.042491 | \n",
+ " 5359.167068 | \n",
+ " 0.039801 | \n",
+ " 5475.811021 | \n",
+ " 0.018902 | \n",
+ " 5618.005145 | \n",
+ " -0.006575 | \n",
+ " 5687.565590 | \n",
+ " -0.019038 | \n",
+ " 2738.215621 | \n",
+ " 0.509396 | \n",
+ " 3798.702668 | \n",
+ " 0.319389 | \n",
+ " 5106.724049 | \n",
+ " 0.085031 | \n",
+ " 5924.946844 | \n",
+ " -0.061569 | \n",
+ " 6350.410974 | \n",
+ " -0.137799 | \n",
+ " 6250.138777 | \n",
+ " -0.119834 | \n",
+ " 6173.995273 | \n",
+ " -0.106191 | \n",
+ " 6007.253773 | \n",
+ " -0.076316 | \n",
+ " 5874.695827 | \n",
+ " -0.052566 | \n",
+ " 5559.283516 | \n",
+ " 0.003946 | \n",
+ " 5589.440875 | \n",
+ " -0.001457 | \n",
+ " 0.097250 | \n",
+ " 0.999983 | \n",
+ " 1615.258137 | \n",
+ " 0.710595 | \n",
+ " 2988.046101 | \n",
+ " 0.464634 | \n",
+ " 3961.078843 | \n",
+ " 0.290296 | \n",
+ " 4916.360392 | \n",
+ " 0.119139 | \n",
+ " 5129.675910 | \n",
+ " 0.080919 | \n",
+ " 5402.084447 | \n",
+ " 0.032112 | \n",
+ " 5347.120892 | \n",
+ " 0.041960 | \n",
+ " 5635.222335 | \n",
+ " -0.009659 | \n",
+ " 5650.083279 | \n",
+ " -0.012322 | \n",
+ " 5611.310265 | \n",
+ " -0.005375 | \n",
+ " 2193.167972 | \n",
+ " 0.607051 | \n",
+ " 3380.287738 | \n",
+ " 0.394356 | \n",
+ " 4332.850804 | \n",
+ " 0.223686 | \n",
+ " 5002.140836 | \n",
+ " 0.103769 | \n",
+ " 5500.719456 | \n",
+ " 0.014439 | \n",
+ " 5462.943959 | \n",
+ " 0.021208 | \n",
+ " 5509.389569 | \n",
+ " 0.012886 | \n",
+ " 5502.215052 | \n",
+ " 0.014171 | \n",
+ " 5581.847580 | \n",
+ " -0.000096 | \n",
+ " 5593.342518 | \n",
+ " -0.002156 | \n",
+ " 5624.090066 | \n",
+ " -0.007665 | \n",
+ " 9.586439 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 4198.773435 | \n",
+ " 0.313618 | \n",
+ " 5217.671821 | \n",
+ " 0.147057 | \n",
+ " 5693.938662 | \n",
+ " 0.069200 | \n",
+ " 6112.809648 | \n",
+ " 0.000727 | \n",
+ " 6071.081040 | \n",
+ " 0.007548 | \n",
+ " 6126.095327 | \n",
+ " -0.001445 | \n",
+ " 6212.118697 | \n",
+ " -0.015508 | \n",
+ " 6156.865589 | \n",
+ " -0.006475 | \n",
+ " 6109.418689 | \n",
+ " 0.001281 | \n",
+ " 6148.928735 | \n",
+ " -0.005178 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 4451.421766 | \n",
+ " 0.272317 | \n",
+ " 5624.555118 | \n",
+ " 0.080542 | \n",
+ " 6568.669569 | \n",
+ " -0.073794 | \n",
+ " 7205.254833 | \n",
+ " -0.177858 | \n",
+ " 7368.282965 | \n",
+ " -0.204508 | \n",
+ " 7365.857893 | \n",
+ " -0.204112 | \n",
+ " 7235.050354 | \n",
+ " -0.182728 | \n",
+ " 6319.121485 | \n",
+ " -0.033000 | \n",
+ " 6286.420406 | \n",
+ " -0.027654 | \n",
+ " 6120.597362 | \n",
+ " -0.000547 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 4729.606612 | \n",
+ " 0.226842 | \n",
+ " 5215.482242 | \n",
+ " 0.147414 | \n",
+ " 5564.663910 | \n",
+ " 0.090333 | \n",
+ " 6160.474136 | \n",
+ " -0.007065 | \n",
+ " 6270.020011 | \n",
+ " -0.024973 | \n",
+ " 6650.748667 | \n",
+ " -0.087211 | \n",
+ " 6412.670943 | \n",
+ " -0.048292 | \n",
+ " 6193.253786 | \n",
+ " -0.012424 | \n",
+ " 6116.982147 | \n",
+ " 0.000044 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 4248.412261 | \n",
+ " 0.305503 | \n",
+ " 5171.726569 | \n",
+ " 0.154567 | \n",
+ " 5755.292147 | \n",
+ " 0.059171 | \n",
+ " 6204.660479 | \n",
+ " -0.014289 | \n",
+ " 6181.820292 | \n",
+ " -0.010555 | \n",
+ " 6215.849342 | \n",
+ " -0.016118 | \n",
+ " 6231.571125 | \n",
+ " -0.018688 | \n",
+ " 6159.118213 | \n",
+ " -0.006844 | \n",
+ " 6128.387250 | \n",
+ " -0.001820 | \n",
+ " 6120.715936 | \n",
+ " -0.000566 | \n",
+ " 9.422463 | \n",
+ " 6121.822228 | \n",
+ " -0.000747 | \n",
+ " 4489.403810 | \n",
+ " 0.266108 | \n",
+ " 3884.769653 | \n",
+ " 0.364949 | \n",
+ " 3566.339313 | \n",
+ " 0.417003 | \n",
+ " 3573.502718 | \n",
+ " 0.415832 | \n",
+ " 3729.050354 | \n",
+ " 0.390405 | \n",
+ " 3612.189687 | \n",
+ " 0.409508 | \n",
+ " 3554.957763 | \n",
+ " 0.418864 | \n",
+ " 3565.914084 | \n",
+ " 0.417073 | \n",
+ " 3533.556383 | \n",
+ " 0.422362 | \n",
+ " 3509.831927 | \n",
+ " 0.426241 | \n",
+ " 6124.876390 | \n",
+ " -0.001246 | \n",
+ " 4415.673403 | \n",
+ " 0.278161 | \n",
+ " 3927.760143 | \n",
+ " 0.357921 | \n",
+ " 3539.162252 | \n",
+ " 0.421446 | \n",
+ " 3418.743202 | \n",
+ " 0.441131 | \n",
+ " 3358.897459 | \n",
+ " 0.450914 | \n",
+ " 3510.708076 | \n",
+ " 0.426097 | \n",
+ " 3617.307137 | \n",
+ " 0.408671 | \n",
+ " 3740.467102 | \n",
+ " 0.388538 | \n",
+ " 3526.414124 | \n",
+ " 0.423530 | \n",
+ " 3546.190517 | \n",
+ " 0.420297 | \n",
+ " 6117.889522 | \n",
+ " -0.000104 | \n",
+ " 4699.814977 | \n",
+ " 0.231712 | \n",
+ " 4347.479047 | \n",
+ " 0.289309 | \n",
+ " 3463.455559 | \n",
+ " 0.433822 | \n",
+ " 3758.003038 | \n",
+ " 0.385672 | \n",
+ " 4026.467096 | \n",
+ " 0.341785 | \n",
+ " 4151.956487 | \n",
+ " 0.321271 | \n",
+ " 4270.034114 | \n",
+ " 0.301969 | \n",
+ " 4474.321171 | \n",
+ " 0.268574 | \n",
+ " 4369.924399 | \n",
+ " 0.285640 | \n",
+ " 4204.805826 | \n",
+ " 0.312632 | \n",
+ " 6118.188308 | \n",
+ " -0.000153 | \n",
+ " 4473.629476 | \n",
+ " 0.268687 | \n",
+ " 3891.952087 | \n",
+ " 0.363775 | \n",
+ " 3520.269715 | \n",
+ " 0.424534 | \n",
+ " 3479.444407 | \n",
+ " 0.431208 | \n",
+ " 3549.656569 | \n",
+ " 0.419730 | \n",
+ " 3526.783158 | \n",
+ " 0.423470 | \n",
+ " 3512.839878 | \n",
+ " 0.425749 | \n",
+ " 3524.189811 | \n",
+ " 0.423893 | \n",
+ " 3486.336515 | \n",
+ " 0.430081 | \n",
+ " 3474.597817 | \n",
+ " 0.432000 | \n",
+ " 9.847889 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -2634,194 +7034,8 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
- " 4690 | \n",
- " 0.249166 | \n",
- " 1599.333649 | \n",
- " 0.737912 | \n",
- " 3175.230208 | \n",
- " 0.479666 | \n",
- " 4498.675276 | \n",
- " 0.262789 | \n",
- " 5261.137462 | \n",
- " 0.137842 | \n",
- " 5924.955983 | \n",
- " 0.029060 | \n",
- " 6212.097890 | \n",
- " -0.017995 | \n",
- " 6262.068654 | \n",
- " -0.026184 | \n",
- " 6179.049182 | \n",
- " -0.012579 | \n",
- " 6235.406215 | \n",
- " -0.021815 | \n",
- " 6213.565248 | \n",
- " -0.018235 | \n",
- " 6136.821625 | \n",
- " -0.005659 | \n",
- " 2821.915630 | \n",
- " 0.537564 | \n",
- " 4124.907264 | \n",
- " 0.324039 | \n",
- " 5934.906752 | \n",
- " 0.027429 | \n",
- " 6682.422829 | \n",
- " -0.095068 | \n",
- " 7204.488112 | \n",
- " -0.180621 | \n",
- " 7443.348015 | \n",
- " -0.219764 | \n",
- " 7525.682868 | \n",
- " -0.233256 | \n",
- " 7552.747816 | \n",
- " -0.237691 | \n",
- " 7347.797853 | \n",
- " -0.204105 | \n",
- " 6955.511368 | \n",
- " -0.139820 | \n",
- " 6102.287573 | \n",
- " 0.0 | \n",
- " 0.760518 | \n",
- " 0.999875 | \n",
- " 1782.617426 | \n",
- " 0.707877 | \n",
- " 3201.913810 | \n",
- " 0.475293 | \n",
- " 4730.471547 | \n",
- " 0.224804 | \n",
- " 5150.386860 | \n",
- " 0.155991 | \n",
- " 5606.040199 | \n",
- " 0.081322 | \n",
- " 5963.154321 | \n",
- " 0.022800 | \n",
- " 6399.094632 | \n",
- " -0.048639 | \n",
- " 6741.407424 | \n",
- " -0.104734 | \n",
- " 6921.960510 | \n",
- " -0.134322 | \n",
- " 7157.760530 | \n",
- " -0.172963 | \n",
- " 2334.402428 | \n",
- " 0.617455 | \n",
- " 3761.718243 | \n",
- " 0.383556 | \n",
- " 5045.947750 | \n",
- " 0.173106 | \n",
- " 5554.918333 | \n",
- " 0.089699 | \n",
- " 6154.518735 | \n",
- " -0.008559 | \n",
- " 6418.420962 | \n",
- " -0.051806 | \n",
- " 6428.170085 | \n",
- " -0.053403 | \n",
- " 6373.102912 | \n",
- " -0.044379 | \n",
- " 6360.759368 | \n",
- " -0.042357 | \n",
- " 6269.951470 | \n",
- " -0.027476 | \n",
- " 6131.312645 | \n",
- " -0.004756 | \n",
- " 10.695844 | \n",
- " 3072.457734 | \n",
- " 0.448450 | \n",
- " 3743.320860 | \n",
- " 0.328020 | \n",
- " 4211.329333 | \n",
- " 0.244006 | \n",
- " 4765.872128 | \n",
- " 0.144457 | \n",
- " 5236.877977 | \n",
- " 0.059905 | \n",
- " 5625.037238 | \n",
- " -0.009775 | \n",
- " 5521.985960 | \n",
- " 0.008724 | \n",
- " 5545.446533 | \n",
- " 0.004512 | \n",
- " 5653.778023 | \n",
- " -0.014935 | \n",
- " 5661.451333 | \n",
- " -0.016312 | \n",
- " 5664.609603 | \n",
- " -0.016879 | \n",
- " 3213.858553 | \n",
- " 0.423066 | \n",
- " 4218.066221 | \n",
- " 0.242796 | \n",
- " 5356.336721 | \n",
- " 0.038460 | \n",
- " 5997.063026 | \n",
- " -0.076559 | \n",
- " 6524.414652 | \n",
- " -0.171227 | \n",
- " 7015.708280 | \n",
- " -0.259421 | \n",
- " 7106.531998 | \n",
- " -0.275725 | \n",
- " 6990.755293 | \n",
- " -0.254941 | \n",
- " 6853.979093 | \n",
- " -0.230388 | \n",
- " 6484.153190 | \n",
- " -0.163999 | \n",
- " 5585.176699 | \n",
- " -0.002620 | \n",
- " 3725.748845 | \n",
- " 0.331174 | \n",
- " 4433.523117 | \n",
- " 0.204119 | \n",
- " 5404.224345 | \n",
- " 0.029864 | \n",
- " 6252.311144 | \n",
- " -0.122380 | \n",
- " 6135.927928 | \n",
- " -0.101488 | \n",
- " 6393.470622 | \n",
- " -0.147720 | \n",
- " 6529.782934 | \n",
- " -0.172190 | \n",
- " 6440.441698 | \n",
- " -0.156152 | \n",
- " 6627.164328 | \n",
- " -0.189672 | \n",
- " 6234.587550 | \n",
- " -0.119198 | \n",
- " 6392.430662 | \n",
- " -0.147533 | \n",
- " 3043.279335 | \n",
- " 0.453687 | \n",
- " 3916.359829 | \n",
- " 0.296957 | \n",
- " 4555.396175 | \n",
- " 0.182241 | \n",
- " 5116.362836 | \n",
- " 0.081539 | \n",
- " 5520.772874 | \n",
- " 0.008942 | \n",
- " 5789.702012 | \n",
- " -0.039335 | \n",
- " 5781.533396 | \n",
- " -0.037869 | \n",
- " 5764.376455 | \n",
- " -0.034789 | \n",
- " 5799.731329 | \n",
- " -0.041135 | \n",
- " 5737.201421 | \n",
- " -0.029910 | \n",
- " 5655.363927 | \n",
- " -0.015219 | \n",
- " 7.402059 | \n",
- " 6 | \n",
" NaN | \n",
- "
\n",
- " \n",
- " 67 | \n",
" NaN | \n",
- " keep_all_rows | \n",
- " 0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -2831,302 +7045,7 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
- " RF_plus | \n",
- " Kernel_SHAP_RF_plus | \n",
- " 296 | \n",
- " 100 | \n",
- " 10 | \n",
- " 6 | \n",
- " 3043.279335 | \n",
- " 0.453687 | \n",
- " 19.0 | \n",
- " 18.0 | \n",
- " 119.0 | \n",
- " 77.0 | \n",
- " 71.0 | \n",
- " 103.0 | \n",
- " 33.0 | \n",
- " 126.0 | \n",
- " 48.0 | \n",
- " 36.0 | \n",
- " 59.0 | \n",
- " 49.0 | \n",
- " 62.0 | \n",
- " 42.0 | \n",
- " 13.0 | \n",
- " 82.0 | \n",
- " 22.0 | \n",
- " 123.0 | \n",
- " 75.0 | \n",
- " 137.0 | \n",
- " 134.0 | \n",
- " 38.0 | \n",
- " 2.0 | \n",
- " 79.0 | \n",
- " 138.0 | \n",
- " 88.0 | \n",
- " 54.0 | \n",
- " 55.0 | \n",
- " 84.0 | \n",
- " 50.0 | \n",
- " 114.0 | \n",
- " 144.0 | \n",
- " 7.0 | \n",
- " 53.0 | \n",
- " 5.0 | \n",
- " 124.0 | \n",
- " 104.0 | \n",
- " 44.0 | \n",
- " 60.0 | \n",
- " 99.0 | \n",
- " 93.0 | \n",
- " 112.0 | \n",
- " 128.0 | \n",
- " 85.0 | \n",
- " 76.0 | \n",
- " 25.0 | \n",
- " 92.0 | \n",
- " 86.0 | \n",
- " 127.0 | \n",
- " 115.0 | \n",
- " 41.0 | \n",
- " 97.0 | \n",
- " 113.0 | \n",
- " 118.0 | \n",
- " 135.0 | \n",
- " 101.0 | \n",
- " 8.0 | \n",
- " 27.0 | \n",
- " 72.0 | \n",
- " 94.0 | \n",
- " 133.0 | \n",
- " 43.0 | \n",
- " 120.0 | \n",
- " 51.0 | \n",
- " 132.0 | \n",
- " 61.0 | \n",
- " 83.0 | \n",
- " 32.0 | \n",
- " 45.0 | \n",
- " 95.0 | \n",
- " 30.0 | \n",
- " 31.0 | \n",
- " 90.0 | \n",
- " 129.0 | \n",
- " 100.0 | \n",
- " 96.0 | \n",
- " 14.0 | \n",
- " 39.0 | \n",
- " 80.0 | \n",
- " 56.0 | \n",
- " 35.0 | \n",
- " 139.0 | \n",
- " 16.0 | \n",
- " 70.0 | \n",
- " 46.0 | \n",
- " 69.0 | \n",
- " 6.0 | \n",
- " 23.0 | \n",
- " 52.0 | \n",
- " 29.0 | \n",
- " 15.0 | \n",
- " 66.0 | \n",
- " 68.0 | \n",
- " 37.0 | \n",
- " 64.0 | \n",
- " 17.0 | \n",
- " 4.0 | \n",
- " 145.0 | \n",
- " 47.0 | \n",
- " 63.0 | \n",
- " 188 | \n",
- " 277.196261 | \n",
- " 1599.333649 | \n",
- " 0.737912 | \n",
- " 3109.607702 | \n",
- " 0.490419 | \n",
- " 4278.810212 | \n",
- " 0.298819 | \n",
- " 5024.113229 | \n",
- " 0.176684 | \n",
- " 5528.180545 | \n",
- " 0.094081 | \n",
- " 5710.608596 | \n",
- " 0.064186 | \n",
- " 5874.069955 | \n",
- " 0.037399 | \n",
- " 5921.729102 | \n",
- " 0.029589 | \n",
- " 5990.038030 | \n",
- " 0.018395 | \n",
- " 6126.092314 | \n",
- " -0.003901 | \n",
- " 6136.821625 | \n",
- " -0.005659 | \n",
- " 2821.915630 | \n",
- " 0.537564 | \n",
- " 4042.670841 | \n",
- " 0.337516 | \n",
- " 5643.649191 | \n",
- " 0.075158 | \n",
- " 6612.534967 | \n",
- " -0.083616 | \n",
- " 7126.165388 | \n",
- " -0.167786 | \n",
- " 7249.087498 | \n",
- " -0.187930 | \n",
- " 7278.281425 | \n",
- " -0.192714 | \n",
- " 6820.752066 | \n",
- " -0.117737 | \n",
- " 6559.088545 | \n",
- " -0.074857 | \n",
- " 6186.218071 | \n",
- " -0.013754 | \n",
- " 6102.287573 | \n",
- " 0.0 | \n",
- " 0.760518 | \n",
- " 0.999875 | \n",
- " 1830.868812 | \n",
- " 0.699970 | \n",
- " 3019.931424 | \n",
- " 0.505115 | \n",
- " 4240.653693 | \n",
- " 0.305071 | \n",
- " 4955.577984 | \n",
- " 0.187915 | \n",
- " 5682.969251 | \n",
- " 0.068715 | \n",
- " 6023.360442 | \n",
- " 0.012934 | \n",
- " 6165.455206 | \n",
- " -0.010351 | \n",
- " 6512.064765 | \n",
- " -0.067151 | \n",
- " 6924.629590 | \n",
- " -0.134760 | \n",
- " 7157.760530 | \n",
- " -0.172963 | \n",
- " 2334.402428 | \n",
- " 0.617455 | \n",
- " 3673.127492 | \n",
- " 0.398074 | \n",
- " 4901.292728 | \n",
- " 0.196811 | \n",
- " 5568.985794 | \n",
- " 0.087394 | \n",
- " 5933.849628 | \n",
- " 0.027602 | \n",
- " 6067.913538 | \n",
- " 0.005633 | \n",
- " 6195.677726 | \n",
- " -0.015304 | \n",
- " 6184.703036 | \n",
- " -0.013506 | \n",
- " 6165.895689 | \n",
- " -0.010424 | \n",
- " 6141.011126 | \n",
- " -0.006346 | \n",
- " 6131.312645 | \n",
- " -0.004756 | \n",
- " 10.828993 | \n",
- " 3074.549811 | \n",
- " 0.439991 | \n",
- " 3824.972040 | \n",
- " 0.303307 | \n",
- " 4273.545813 | \n",
- " 0.221602 | \n",
- " 4822.571646 | \n",
- " 0.121601 | \n",
- " 5169.557621 | \n",
- " 0.058400 | \n",
- " 5364.977537 | \n",
- " 0.022805 | \n",
- " 5362.147595 | \n",
- " 0.023321 | \n",
- " 5383.491593 | \n",
- " 0.019433 | \n",
- " 5405.576376 | \n",
- " 0.015410 | \n",
- " 5547.677265 | \n",
- " -0.010472 | \n",
- " 5648.814576 | \n",
- " -0.028894 | \n",
- " 3438.229965 | \n",
- " 0.373749 | \n",
- " 4269.577351 | \n",
- " 0.222325 | \n",
- " 5222.916628 | \n",
- " 0.048681 | \n",
- " 5812.610512 | \n",
- " -0.058728 | \n",
- " 6323.222346 | \n",
- " -0.151733 | \n",
- " 6789.017275 | \n",
- " -0.236574 | \n",
- " 6888.956923 | \n",
- " -0.254778 | \n",
- " 6342.579611 | \n",
- " -0.155259 | \n",
- " 5805.435651 | \n",
- " -0.057421 | \n",
- " 5647.333250 | \n",
- " -0.028624 | \n",
- " 5535.318508 | \n",
- " -0.008221 | \n",
- " 3761.115159 | \n",
- " 0.314938 | \n",
- " 4551.081588 | \n",
- " 0.171051 | \n",
- " 5212.816093 | \n",
- " 0.050520 | \n",
- " 5727.578800 | \n",
- " -0.043240 | \n",
- " 6311.016611 | \n",
- " -0.149510 | \n",
- " 6614.314282 | \n",
- " -0.204753 | \n",
- " 6483.378328 | \n",
- " -0.180904 | \n",
- " 5960.523436 | \n",
- " -0.085670 | \n",
- " 6015.960917 | \n",
- " -0.095767 | \n",
- " 6115.491296 | \n",
- " -0.113896 | \n",
- " 6154.257530 | \n",
- " -0.120957 | \n",
- " 3139.516608 | \n",
- " 0.428158 | \n",
- " 3949.965025 | \n",
- " 0.280540 | \n",
- " 4609.805293 | \n",
- " 0.160355 | \n",
- " 5102.378012 | \n",
- " 0.070636 | \n",
- " 5422.380406 | \n",
- " 0.012350 | \n",
- " 5611.746572 | \n",
- " -0.022142 | \n",
- " 5650.413900 | \n",
- " -0.029185 | \n",
- " 5624.395688 | \n",
- " -0.024446 | \n",
- " 5597.750571 | \n",
- " -0.019593 | \n",
- " 5626.025263 | \n",
- " -0.024743 | \n",
- " 5636.734002 | \n",
- " -0.026693 | \n",
- " 7.036491 | \n",
- " 6 | \n",
- " RandomForestRegressor(max_features=0.33, min_s... | \n",
- "
\n",
- " \n",
- " 68 | \n",
" NaN | \n",
- " keep_all_rows | \n",
- " 0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -3136,302 +7055,7 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
- " RF_plus | \n",
- " LFI_with_raw_RF_plus | \n",
- " 296 | \n",
- " 100 | \n",
- " 10 | \n",
- " 6 | \n",
- " 3043.279335 | \n",
- " 0.453687 | \n",
- " 19.0 | \n",
- " 18.0 | \n",
- " 119.0 | \n",
- " 77.0 | \n",
- " 71.0 | \n",
- " 103.0 | \n",
- " 33.0 | \n",
- " 126.0 | \n",
- " 48.0 | \n",
- " 36.0 | \n",
- " 59.0 | \n",
- " 49.0 | \n",
- " 62.0 | \n",
- " 42.0 | \n",
- " 13.0 | \n",
- " 82.0 | \n",
- " 22.0 | \n",
- " 123.0 | \n",
- " 75.0 | \n",
- " 137.0 | \n",
- " 134.0 | \n",
- " 38.0 | \n",
- " 2.0 | \n",
- " 79.0 | \n",
- " 138.0 | \n",
- " 88.0 | \n",
- " 54.0 | \n",
- " 55.0 | \n",
- " 84.0 | \n",
- " 50.0 | \n",
- " 114.0 | \n",
- " 144.0 | \n",
- " 7.0 | \n",
- " 53.0 | \n",
- " 5.0 | \n",
- " 124.0 | \n",
- " 104.0 | \n",
- " 44.0 | \n",
- " 60.0 | \n",
- " 99.0 | \n",
- " 93.0 | \n",
- " 112.0 | \n",
- " 128.0 | \n",
- " 85.0 | \n",
- " 76.0 | \n",
- " 25.0 | \n",
- " 92.0 | \n",
- " 86.0 | \n",
- " 127.0 | \n",
- " 115.0 | \n",
- " 41.0 | \n",
- " 97.0 | \n",
- " 113.0 | \n",
- " 118.0 | \n",
- " 135.0 | \n",
- " 101.0 | \n",
- " 8.0 | \n",
- " 27.0 | \n",
- " 72.0 | \n",
- " 94.0 | \n",
- " 133.0 | \n",
- " 43.0 | \n",
- " 120.0 | \n",
- " 51.0 | \n",
- " 132.0 | \n",
- " 61.0 | \n",
- " 83.0 | \n",
- " 32.0 | \n",
- " 45.0 | \n",
- " 95.0 | \n",
- " 30.0 | \n",
- " 31.0 | \n",
- " 90.0 | \n",
- " 129.0 | \n",
- " 100.0 | \n",
- " 96.0 | \n",
- " 14.0 | \n",
- " 39.0 | \n",
- " 80.0 | \n",
- " 56.0 | \n",
- " 35.0 | \n",
- " 139.0 | \n",
- " 16.0 | \n",
- " 70.0 | \n",
- " 46.0 | \n",
- " 69.0 | \n",
- " 6.0 | \n",
- " 23.0 | \n",
- " 52.0 | \n",
- " 29.0 | \n",
- " 15.0 | \n",
- " 66.0 | \n",
- " 68.0 | \n",
- " 37.0 | \n",
- " 64.0 | \n",
- " 17.0 | \n",
- " 4.0 | \n",
- " 145.0 | \n",
- " 47.0 | \n",
- " 63.0 | \n",
- " 188 | \n",
- " 1.481301 | \n",
- " 1599.333649 | \n",
- " 0.737912 | \n",
- " 2929.545377 | \n",
- " 0.519927 | \n",
- " 4293.008635 | \n",
- " 0.296492 | \n",
- " 4993.430906 | \n",
- " 0.181712 | \n",
- " 5530.065550 | \n",
- " 0.093772 | \n",
- " 5805.377507 | \n",
- " 0.048656 | \n",
- " 5901.229975 | \n",
- " 0.032948 | \n",
- " 5971.856480 | \n",
- " 0.021374 | \n",
- " 6054.179537 | \n",
- " 0.007884 | \n",
- " 6175.355063 | \n",
- " -0.011974 | \n",
- " 6136.821625 | \n",
- " -0.005659 | \n",
- " 2821.915630 | \n",
- " 0.537564 | \n",
- " 4061.883737 | \n",
- " 0.334367 | \n",
- " 5760.011411 | \n",
- " 0.056090 | \n",
- " 6607.114189 | \n",
- " -0.082727 | \n",
- " 7187.319599 | \n",
- " -0.177807 | \n",
- " 7383.018224 | \n",
- " -0.209877 | \n",
- " 7452.938431 | \n",
- " -0.221335 | \n",
- " 7070.721750 | \n",
- " -0.158700 | \n",
- " 6725.906785 | \n",
- " -0.102194 | \n",
- " 6256.765405 | \n",
- " -0.025315 | \n",
- " 6102.287573 | \n",
- " 0.0 | \n",
- " 0.760518 | \n",
- " 0.999875 | \n",
- " 1549.952598 | \n",
- " 0.746005 | \n",
- " 2949.589294 | \n",
- " 0.516642 | \n",
- " 4180.439924 | \n",
- " 0.314939 | \n",
- " 5094.934816 | \n",
- " 0.165078 | \n",
- " 5662.407971 | \n",
- " 0.072084 | \n",
- " 5954.963272 | \n",
- " 0.024142 | \n",
- " 6157.649217 | \n",
- " -0.009072 | \n",
- " 6483.893137 | \n",
- " -0.062535 | \n",
- " 6980.145851 | \n",
- " -0.143857 | \n",
- " 7157.760530 | \n",
- " -0.172963 | \n",
- " 2334.402428 | \n",
- " 0.617455 | \n",
- " 3582.949000 | \n",
- " 0.412851 | \n",
- " 4923.427170 | \n",
- " 0.193183 | \n",
- " 5566.165474 | \n",
- " 0.087856 | \n",
- " 5979.565894 | \n",
- " 0.020111 | \n",
- " 6150.733264 | \n",
- " -0.007939 | \n",
- " 6225.990012 | \n",
- " -0.020271 | \n",
- " 6222.193823 | \n",
- " -0.019649 | \n",
- " 6178.858171 | \n",
- " -0.012548 | \n",
- " 6164.131500 | \n",
- " -0.010135 | \n",
- " 6131.312645 | \n",
- " -0.004756 | \n",
- " 10.817527 | \n",
- " 3074.549811 | \n",
- " 0.439991 | \n",
- " 3677.383895 | \n",
- " 0.330189 | \n",
- " 4223.973426 | \n",
- " 0.230631 | \n",
- " 4853.249242 | \n",
- " 0.116013 | \n",
- " 5184.298032 | \n",
- " 0.055715 | \n",
- " 5471.391949 | \n",
- " 0.003422 | \n",
- " 5443.474923 | \n",
- " 0.008507 | \n",
- " 5455.547129 | \n",
- " 0.006308 | \n",
- " 5499.562086 | \n",
- " -0.001709 | \n",
- " 5564.283426 | \n",
- " -0.013497 | \n",
- " 5648.814576 | \n",
- " -0.028894 | \n",
- " 3438.229965 | \n",
- " 0.373749 | \n",
- " 4250.446715 | \n",
- " 0.225809 | \n",
- " 5168.535770 | \n",
- " 0.058586 | \n",
- " 5904.704003 | \n",
- " -0.075502 | \n",
- " 6346.397918 | \n",
- " -0.155954 | \n",
- " 6559.339739 | \n",
- " -0.194740 | \n",
- " 6702.852473 | \n",
- " -0.220880 | \n",
- " 6652.209705 | \n",
- " -0.211656 | \n",
- " 6360.483378 | \n",
- " -0.158520 | \n",
- " 5807.268863 | \n",
- " -0.057755 | \n",
- " 5535.318508 | \n",
- " -0.008221 | \n",
- " 3761.115159 | \n",
- " 0.314938 | \n",
- " 4484.427719 | \n",
- " 0.183191 | \n",
- " 5230.083512 | \n",
- " 0.047375 | \n",
- " 6147.504065 | \n",
- " -0.119727 | \n",
- " 6596.737184 | \n",
- " -0.201552 | \n",
- " 6460.519172 | \n",
- " -0.176740 | \n",
- " 6583.652258 | \n",
- " -0.199168 | \n",
- " 6573.851529 | \n",
- " -0.197383 | \n",
- " 6295.371009 | \n",
- " -0.146660 | \n",
- " 6204.552633 | \n",
- " -0.130118 | \n",
- " 6154.257530 | \n",
- " -0.120957 | \n",
- " 3139.516608 | \n",
- " 0.428158 | \n",
- " 3882.799563 | \n",
- " 0.292774 | \n",
- " 4562.861560 | \n",
- " 0.168905 | \n",
- " 5160.712830 | \n",
- " 0.060011 | \n",
- " 5366.841728 | \n",
- " 0.022466 | \n",
- " 5591.524535 | \n",
- " -0.018459 | \n",
- " 5634.800732 | \n",
- " -0.026341 | \n",
- " 5614.899058 | \n",
- " -0.022716 | \n",
- " 5613.153894 | \n",
- " -0.022399 | \n",
- " 5620.507263 | \n",
- " -0.023738 | \n",
- " 5636.734002 | \n",
- " -0.026693 | \n",
- " 7.033576 | \n",
- " 6 | \n",
- " RandomForestRegressor(max_features=0.33, min_s... | \n",
- "
\n",
- " \n",
- " 69 | \n",
" NaN | \n",
- " keep_all_rows | \n",
- " 0 | \n",
" NaN | \n",
" NaN | \n",
" NaN | \n",
@@ -3441,300 +7065,12 @@
" NaN | \n",
" NaN | \n",
" NaN | \n",
- " RF_plus | \n",
- " LIME_RF_plus | \n",
- " 296 | \n",
- " 100 | \n",
" 10 | \n",
- " 6 | \n",
- " 3043.279335 | \n",
- " 0.453687 | \n",
- " 19.0 | \n",
- " 18.0 | \n",
- " 119.0 | \n",
- " 77.0 | \n",
- " 71.0 | \n",
- " 103.0 | \n",
- " 33.0 | \n",
- " 126.0 | \n",
- " 48.0 | \n",
- " 36.0 | \n",
- " 59.0 | \n",
- " 49.0 | \n",
- " 62.0 | \n",
- " 42.0 | \n",
- " 13.0 | \n",
- " 82.0 | \n",
- " 22.0 | \n",
- " 123.0 | \n",
- " 75.0 | \n",
- " 137.0 | \n",
- " 134.0 | \n",
- " 38.0 | \n",
- " 2.0 | \n",
- " 79.0 | \n",
- " 138.0 | \n",
- " 88.0 | \n",
- " 54.0 | \n",
- " 55.0 | \n",
- " 84.0 | \n",
- " 50.0 | \n",
- " 114.0 | \n",
- " 144.0 | \n",
- " 7.0 | \n",
- " 53.0 | \n",
- " 5.0 | \n",
- " 124.0 | \n",
- " 104.0 | \n",
- " 44.0 | \n",
- " 60.0 | \n",
- " 99.0 | \n",
- " 93.0 | \n",
- " 112.0 | \n",
- " 128.0 | \n",
- " 85.0 | \n",
- " 76.0 | \n",
- " 25.0 | \n",
- " 92.0 | \n",
- " 86.0 | \n",
- " 127.0 | \n",
- " 115.0 | \n",
- " 41.0 | \n",
- " 97.0 | \n",
- " 113.0 | \n",
- " 118.0 | \n",
- " 135.0 | \n",
- " 101.0 | \n",
- " 8.0 | \n",
- " 27.0 | \n",
- " 72.0 | \n",
- " 94.0 | \n",
- " 133.0 | \n",
- " 43.0 | \n",
- " 120.0 | \n",
- " 51.0 | \n",
- " 132.0 | \n",
- " 61.0 | \n",
- " 83.0 | \n",
- " 32.0 | \n",
- " 45.0 | \n",
- " 95.0 | \n",
- " 30.0 | \n",
- " 31.0 | \n",
- " 90.0 | \n",
- " 129.0 | \n",
- " 100.0 | \n",
- " 96.0 | \n",
- " 14.0 | \n",
- " 39.0 | \n",
- " 80.0 | \n",
- " 56.0 | \n",
- " 35.0 | \n",
- " 139.0 | \n",
- " 16.0 | \n",
- " 70.0 | \n",
- " 46.0 | \n",
- " 69.0 | \n",
- " 6.0 | \n",
- " 23.0 | \n",
- " 52.0 | \n",
- " 29.0 | \n",
- " 15.0 | \n",
- " 66.0 | \n",
- " 68.0 | \n",
- " 37.0 | \n",
- " 64.0 | \n",
- " 17.0 | \n",
- " 4.0 | \n",
- " 145.0 | \n",
- " 47.0 | \n",
- " 63.0 | \n",
- " 188 | \n",
- " 618.747853 | \n",
- " 1599.333649 | \n",
- " 0.737912 | \n",
- " 2804.384070 | \n",
- " 0.540437 | \n",
- " 3822.906427 | \n",
- " 0.373529 | \n",
- " 4535.926610 | \n",
- " 0.256684 | \n",
- " 5000.666619 | \n",
- " 0.180526 | \n",
- " 5427.487599 | \n",
- " 0.110581 | \n",
- " 5653.479333 | \n",
- " 0.073548 | \n",
- " 5880.020669 | \n",
- " 0.036424 | \n",
- " 5955.174232 | \n",
- " 0.024108 | \n",
- " 6043.195386 | \n",
- " 0.009684 | \n",
- " 6136.821625 | \n",
- " -0.005659 | \n",
- " 2821.915630 | \n",
- " 0.537564 | \n",
- " 3838.501816 | \n",
- " 0.370973 | \n",
- " 5478.137514 | \n",
- " 0.102281 | \n",
- " 6270.632052 | \n",
- " -0.027587 | \n",
- " 6728.929011 | \n",
- " -0.102690 | \n",
- " 7242.790599 | \n",
- " -0.186898 | \n",
- " 7201.354577 | \n",
- " -0.180107 | \n",
- " 7055.655190 | \n",
- " -0.156231 | \n",
- " 6564.300773 | \n",
- " -0.075711 | \n",
- " 6221.826715 | \n",
- " -0.019589 | \n",
- " 6102.287573 | \n",
- " 0.0 | \n",
- " 0.760518 | \n",
- " 0.999875 | \n",
- " 1461.549087 | \n",
- " 0.760492 | \n",
- " 2485.350227 | \n",
- " 0.592718 | \n",
- " 3405.374928 | \n",
- " 0.441951 | \n",
- " 4237.103450 | \n",
- " 0.305653 | \n",
- " 5025.917365 | \n",
- " 0.176388 | \n",
- " 5526.111155 | \n",
- " 0.094420 | \n",
- " 6041.587390 | \n",
- " 0.009947 | \n",
- " 6323.935368 | \n",
- " -0.036322 | \n",
- " 6895.975176 | \n",
- " -0.130064 | \n",
- " 7157.760530 | \n",
- " -0.172963 | \n",
- " 2334.402428 | \n",
- " 0.617455 | \n",
- " 3432.805310 | \n",
- " 0.437456 | \n",
- " 4520.363739 | \n",
- " 0.259235 | \n",
- " 5213.767608 | \n",
- " 0.145604 | \n",
- " 5612.293318 | \n",
- " 0.080297 | \n",
- " 5905.468277 | \n",
- " 0.032253 | \n",
- " 6004.708413 | \n",
- " 0.015991 | \n",
- " 6092.876970 | \n",
- " 0.001542 | \n",
- " 6096.781290 | \n",
- " 0.000902 | \n",
- " 6104.946294 | \n",
- " -0.000436 | \n",
- " 6131.312645 | \n",
- " -0.004756 | \n",
- " 10.869999 | \n",
- " 3074.549811 | \n",
- " 0.439991 | \n",
- " 3488.988909 | \n",
- " 0.364504 | \n",
- " 4038.189629 | \n",
- " 0.264471 | \n",
- " 4713.345462 | \n",
- " 0.141496 | \n",
- " 5046.789311 | \n",
- " 0.080761 | \n",
- " 5304.597975 | \n",
- " 0.033803 | \n",
- " 5388.787525 | \n",
- " 0.018468 | \n",
- " 5465.219576 | \n",
- " 0.004547 | \n",
- " 5509.129123 | \n",
- " -0.003451 | \n",
- " 5521.703510 | \n",
- " -0.005741 | \n",
- " 5648.814576 | \n",
- " -0.028894 | \n",
- " 3438.229965 | \n",
- " 0.373749 | \n",
- " 4154.543994 | \n",
- " 0.243278 | \n",
- " 5271.242084 | \n",
- " 0.039878 | \n",
- " 5923.989444 | \n",
- " -0.079015 | \n",
- " 6127.787889 | \n",
- " -0.116136 | \n",
- " 6595.262987 | \n",
- " -0.201283 | \n",
- " 6947.470195 | \n",
- " -0.265435 | \n",
- " 6558.722886 | \n",
- " -0.194628 | \n",
- " 6060.428514 | \n",
- " -0.103867 | \n",
- " 5729.046317 | \n",
- " -0.043508 | \n",
- " 5535.318508 | \n",
- " -0.008221 | \n",
- " 3761.115159 | \n",
- " 0.314938 | \n",
- " 4499.283634 | \n",
- " 0.180486 | \n",
- " 4657.567836 | \n",
- " 0.151655 | \n",
- " 5698.794307 | \n",
- " -0.037997 | \n",
- " 6048.504854 | \n",
- " -0.101695 | \n",
- " 6602.231271 | \n",
- " -0.202552 | \n",
- " 6440.659192 | \n",
- " -0.173123 | \n",
- " 6118.444678 | \n",
- " -0.114434 | \n",
- " 6293.345882 | \n",
- " -0.146291 | \n",
- " 6083.916220 | \n",
- " -0.108145 | \n",
- " 6154.257530 | \n",
- " -0.120957 | \n",
- " 3139.516608 | \n",
- " 0.428158 | \n",
- " 3761.727998 | \n",
- " 0.314826 | \n",
- " 4420.406856 | \n",
- " 0.194852 | \n",
- " 5086.133038 | \n",
- " 0.073595 | \n",
- " 5394.059982 | \n",
- " 0.017508 | \n",
- " 5571.039679 | \n",
- " -0.014728 | \n",
- " 5549.016093 | \n",
- " -0.010716 | \n",
- " 5631.833473 | \n",
- " -0.025801 | \n",
- " 5591.152466 | \n",
- " -0.018391 | \n",
- " 5590.145323 | \n",
- " -0.018208 | \n",
- " 5636.734002 | \n",
- " -0.026693 | \n",
- " 6.885340 | \n",
- " 6 | \n",
" RandomForestRegressor(max_features=0.33, min_s... | \n",
"
\n",
" \n",
"\n",
- "70 rows × 302 columns
\n",
+ "70 rows × 580 columns
\n",
""
],
"text/plain": [
@@ -3758,2366 +7094,5135 @@
"3 0.33 42.0 NaN NaN NaN \n",
"4 NaN NaN NaN NaN NaN \n",
".. ... ... ... ... ... \n",
- "65 0.33 42.0 False 0.0 False \n",
- "66 0.33 42.0 NaN NaN NaN \n",
- "67 NaN NaN NaN NaN NaN \n",
- "68 NaN NaN NaN NaN NaN \n",
- "69 NaN NaN NaN NaN NaN \n",
- "\n",
- " sample_split fit_on model fi train_size test_size \\\n",
- "0 oob test RF LFI_with_raw_OOB_RF 296 146 \n",
- "1 NaN NaN RF LFI_with_raw_RF 296 146 \n",
- "2 inbag NaN RF MDI_RF 296 146 \n",
- "3 NaN NaN RF TreeSHAP_RF 296 146 \n",
- "4 NaN NaN RF_plus Kernel_SHAP_RF_plus 296 100 \n",
- ".. ... ... ... ... ... ... \n",
- "65 inbag NaN RF MDI_RF 296 146 \n",
- "66 NaN NaN RF TreeSHAP_RF 296 146 \n",
- "67 NaN NaN RF_plus Kernel_SHAP_RF_plus 296 100 \n",
- "68 NaN NaN RF_plus LFI_with_raw_RF_plus 296 100 \n",
- "69 NaN NaN RF_plus LIME_RF_plus 296 100 \n",
- "\n",
- " num_features data_split_seed test_all_mse test_all_r2 sample_test_0 \\\n",
- "0 10 4 3167.314235 0.445492 NaN \n",
- "1 10 4 3167.314235 0.445492 NaN \n",
- "2 10 4 3167.314235 0.445492 NaN \n",
- "3 10 4 3167.314235 0.445492 NaN \n",
- "4 10 4 3068.863830 0.462728 19.0 \n",
- ".. ... ... ... ... ... \n",
- "65 10 6 3072.457734 0.448450 NaN \n",
- "66 10 6 3072.457734 0.448450 NaN \n",
- "67 10 6 3043.279335 0.453687 19.0 \n",
- "68 10 6 3043.279335 0.453687 19.0 \n",
- "69 10 6 3043.279335 0.453687 19.0 \n",
- "\n",
- " sample_test_1 sample_test_2 sample_test_3 sample_test_4 sample_test_5 \\\n",
- "0 NaN NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN NaN \n",
- "4 18.0 119.0 77.0 71.0 103.0 \n",
- ".. ... ... ... ... ... \n",
- "65 NaN NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN NaN \n",
- "67 18.0 119.0 77.0 71.0 103.0 \n",
- "68 18.0 119.0 77.0 71.0 103.0 \n",
- "69 18.0 119.0 77.0 71.0 103.0 \n",
- "\n",
- " sample_test_6 sample_test_7 sample_test_8 sample_test_9 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 33.0 126.0 48.0 36.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 33.0 126.0 48.0 36.0 \n",
- "68 33.0 126.0 48.0 36.0 \n",
- "69 33.0 126.0 48.0 36.0 \n",
- "\n",
- " sample_test_10 sample_test_11 sample_test_12 sample_test_13 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 59.0 49.0 62.0 42.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 59.0 49.0 62.0 42.0 \n",
- "68 59.0 49.0 62.0 42.0 \n",
- "69 59.0 49.0 62.0 42.0 \n",
- "\n",
- " sample_test_14 sample_test_15 sample_test_16 sample_test_17 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 13.0 82.0 22.0 123.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 13.0 82.0 22.0 123.0 \n",
- "68 13.0 82.0 22.0 123.0 \n",
- "69 13.0 82.0 22.0 123.0 \n",
- "\n",
- " sample_test_18 sample_test_19 sample_test_20 sample_test_21 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 75.0 137.0 134.0 38.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 75.0 137.0 134.0 38.0 \n",
- "68 75.0 137.0 134.0 38.0 \n",
- "69 75.0 137.0 134.0 38.0 \n",
- "\n",
- " sample_test_22 sample_test_23 sample_test_24 sample_test_25 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 2.0 79.0 138.0 88.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 2.0 79.0 138.0 88.0 \n",
- "68 2.0 79.0 138.0 88.0 \n",
- "69 2.0 79.0 138.0 88.0 \n",
- "\n",
- " sample_test_26 sample_test_27 sample_test_28 sample_test_29 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 54.0 55.0 84.0 50.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 54.0 55.0 84.0 50.0 \n",
- "68 54.0 55.0 84.0 50.0 \n",
- "69 54.0 55.0 84.0 50.0 \n",
- "\n",
- " sample_test_30 sample_test_31 sample_test_32 sample_test_33 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 114.0 144.0 7.0 53.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 114.0 144.0 7.0 53.0 \n",
- "68 114.0 144.0 7.0 53.0 \n",
- "69 114.0 144.0 7.0 53.0 \n",
- "\n",
- " sample_test_34 sample_test_35 sample_test_36 sample_test_37 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 5.0 124.0 104.0 44.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 5.0 124.0 104.0 44.0 \n",
- "68 5.0 124.0 104.0 44.0 \n",
- "69 5.0 124.0 104.0 44.0 \n",
- "\n",
- " sample_test_38 sample_test_39 sample_test_40 sample_test_41 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 60.0 99.0 93.0 112.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 60.0 99.0 93.0 112.0 \n",
- "68 60.0 99.0 93.0 112.0 \n",
- "69 60.0 99.0 93.0 112.0 \n",
- "\n",
- " sample_test_42 sample_test_43 sample_test_44 sample_test_45 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 128.0 85.0 76.0 25.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 128.0 85.0 76.0 25.0 \n",
- "68 128.0 85.0 76.0 25.0 \n",
- "69 128.0 85.0 76.0 25.0 \n",
- "\n",
- " sample_test_46 sample_test_47 sample_test_48 sample_test_49 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 92.0 86.0 127.0 115.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 92.0 86.0 127.0 115.0 \n",
- "68 92.0 86.0 127.0 115.0 \n",
- "69 92.0 86.0 127.0 115.0 \n",
- "\n",
- " sample_test_50 sample_test_51 sample_test_52 sample_test_53 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 41.0 97.0 113.0 118.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 41.0 97.0 113.0 118.0 \n",
- "68 41.0 97.0 113.0 118.0 \n",
- "69 41.0 97.0 113.0 118.0 \n",
- "\n",
- " sample_test_54 sample_test_55 sample_test_56 sample_test_57 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 135.0 101.0 8.0 27.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 135.0 101.0 8.0 27.0 \n",
- "68 135.0 101.0 8.0 27.0 \n",
- "69 135.0 101.0 8.0 27.0 \n",
- "\n",
- " sample_test_58 sample_test_59 sample_test_60 sample_test_61 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 72.0 94.0 133.0 43.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 72.0 94.0 133.0 43.0 \n",
- "68 72.0 94.0 133.0 43.0 \n",
- "69 72.0 94.0 133.0 43.0 \n",
- "\n",
- " sample_test_62 sample_test_63 sample_test_64 sample_test_65 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 120.0 51.0 132.0 61.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 120.0 51.0 132.0 61.0 \n",
- "68 120.0 51.0 132.0 61.0 \n",
- "69 120.0 51.0 132.0 61.0 \n",
- "\n",
- " sample_test_66 sample_test_67 sample_test_68 sample_test_69 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 83.0 32.0 45.0 95.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 83.0 32.0 45.0 95.0 \n",
- "68 83.0 32.0 45.0 95.0 \n",
- "69 83.0 32.0 45.0 95.0 \n",
- "\n",
- " sample_test_70 sample_test_71 sample_test_72 sample_test_73 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 30.0 31.0 90.0 129.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 30.0 31.0 90.0 129.0 \n",
- "68 30.0 31.0 90.0 129.0 \n",
- "69 30.0 31.0 90.0 129.0 \n",
- "\n",
- " sample_test_74 sample_test_75 sample_test_76 sample_test_77 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 100.0 96.0 14.0 39.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 100.0 96.0 14.0 39.0 \n",
- "68 100.0 96.0 14.0 39.0 \n",
- "69 100.0 96.0 14.0 39.0 \n",
- "\n",
- " sample_test_78 sample_test_79 sample_test_80 sample_test_81 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 80.0 56.0 35.0 139.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 80.0 56.0 35.0 139.0 \n",
- "68 80.0 56.0 35.0 139.0 \n",
- "69 80.0 56.0 35.0 139.0 \n",
- "\n",
- " sample_test_82 sample_test_83 sample_test_84 sample_test_85 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 16.0 70.0 46.0 69.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 16.0 70.0 46.0 69.0 \n",
- "68 16.0 70.0 46.0 69.0 \n",
- "69 16.0 70.0 46.0 69.0 \n",
- "\n",
- " sample_test_86 sample_test_87 sample_test_88 sample_test_89 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 6.0 23.0 52.0 29.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 6.0 23.0 52.0 29.0 \n",
- "68 6.0 23.0 52.0 29.0 \n",
- "69 6.0 23.0 52.0 29.0 \n",
- "\n",
- " sample_test_90 sample_test_91 sample_test_92 sample_test_93 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 15.0 66.0 68.0 37.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 15.0 66.0 68.0 37.0 \n",
- "68 15.0 66.0 68.0 37.0 \n",
- "69 15.0 66.0 68.0 37.0 \n",
- "\n",
- " sample_test_94 sample_test_95 sample_test_96 sample_test_97 \\\n",
- "0 NaN NaN NaN NaN \n",
- "1 NaN NaN NaN NaN \n",
- "2 NaN NaN NaN NaN \n",
- "3 NaN NaN NaN NaN \n",
- "4 64.0 17.0 4.0 145.0 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN NaN NaN \n",
- "66 NaN NaN NaN NaN \n",
- "67 64.0 17.0 4.0 145.0 \n",
- "68 64.0 17.0 4.0 145.0 \n",
- "69 64.0 17.0 4.0 145.0 \n",
- "\n",
- " sample_test_98 sample_test_99 ablation_seed_0 fi_time \\\n",
- "0 NaN NaN 2405 6.036580 \n",
- "1 NaN NaN 2405 6.758458 \n",
- "2 NaN NaN 2405 2.749065 \n",
- "3 NaN NaN 2405 0.413684 \n",
- "4 47.0 63.0 6733 272.584633 \n",
- ".. ... ... ... ... \n",
- "65 NaN NaN 4690 2.550201 \n",
- "66 NaN NaN 4690 0.249166 \n",
- "67 47.0 63.0 188 277.196261 \n",
- "68 47.0 63.0 188 1.481301 \n",
- "69 47.0 63.0 188 618.747853 \n",
- "\n",
- " RF_Regressor_train_MSE_before_ablation \\\n",
- "0 1635.151982 \n",
- "1 1635.151982 \n",
- "2 1635.151982 \n",
- "3 1635.151982 \n",
- "4 1635.151982 \n",
- ".. ... \n",
- "65 1599.333649 \n",
- "66 1599.333649 \n",
- "67 1599.333649 \n",
- "68 1599.333649 \n",
- "69 1599.333649 \n",
- "\n",
- " RF_Regressor_train_R_2_before_ablation \\\n",
- "0 0.728697 \n",
- "1 0.728697 \n",
- "2 0.728697 \n",
- "3 0.728697 \n",
- "4 0.728697 \n",
- ".. ... \n",
- "65 0.737912 \n",
- "66 0.737912 \n",
- "67 0.737912 \n",
- "68 0.737912 \n",
- "69 0.737912 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_1 \\\n",
- "0 2928.895040 \n",
- "1 3021.720386 \n",
- "2 3133.874535 \n",
- "3 3195.234603 \n",
- "4 3010.018440 \n",
- ".. ... \n",
- "65 3139.907366 \n",
- "66 3175.230208 \n",
- "67 3109.607702 \n",
- "68 2929.545377 \n",
- "69 2804.384070 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_1 \\\n",
- "0 0.514040 \n",
- "1 0.498639 \n",
- "2 0.480030 \n",
- "3 0.469849 \n",
- "4 0.500580 \n",
- ".. ... \n",
- "65 0.485454 \n",
- "66 0.479666 \n",
- "67 0.490419 \n",
- "68 0.519927 \n",
- "69 0.540437 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_2 \\\n",
- "0 4043.923756 \n",
- "1 4123.708913 \n",
- "2 4208.266058 \n",
- "3 4374.383756 \n",
- "4 4081.594103 \n",
- ".. ... \n",
- "65 4304.751910 \n",
- "66 4498.675276 \n",
- "67 4278.810212 \n",
- "68 4293.008635 \n",
- "69 3822.906427 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_2 \\\n",
- "0 0.329035 \n",
- "1 0.315798 \n",
- "2 0.301768 \n",
- "3 0.274206 \n",
- "4 0.322785 \n",
- ".. ... \n",
- "65 0.294568 \n",
- "66 0.262789 \n",
- "67 0.298819 \n",
- "68 0.296492 \n",
- "69 0.373529 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_3 \\\n",
- "0 4919.486722 \n",
- "1 4906.024069 \n",
- "2 5012.797456 \n",
- "3 5218.143321 \n",
- "4 4871.540333 \n",
- ".. ... \n",
- "65 5189.976398 \n",
- "66 5261.137462 \n",
- "67 5024.113229 \n",
- "68 4993.430906 \n",
- "69 4535.926610 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_3 \\\n",
- "0 0.183763 \n",
- "1 0.185996 \n",
- "2 0.168281 \n",
- "3 0.134210 \n",
- "4 0.191718 \n",
- ".. ... \n",
- "65 0.149503 \n",
- "66 0.137842 \n",
- "67 0.176684 \n",
- "68 0.181712 \n",
- "69 0.256684 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_4 \\\n",
- "0 5437.029551 \n",
- "1 5541.504254 \n",
- "2 5621.910172 \n",
- "3 5792.052146 \n",
- "4 5427.925117 \n",
- ".. ... \n",
- "65 5808.092449 \n",
- "66 5924.955983 \n",
- "67 5528.180545 \n",
- "68 5530.065550 \n",
- "69 5000.666619 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_4 \\\n",
- "0 0.097892 \n",
- "1 0.080558 \n",
- "2 0.067217 \n",
- "3 0.038987 \n",
- "4 0.099403 \n",
- ".. ... \n",
- "65 0.048211 \n",
- "66 0.029060 \n",
- "67 0.094081 \n",
- "68 0.093772 \n",
- "69 0.180526 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_5 \\\n",
- "0 5901.392876 \n",
- "1 5961.706039 \n",
- "2 6002.738896 \n",
- "3 6124.433170 \n",
- "4 5806.229855 \n",
- ".. ... \n",
- "65 5979.670912 \n",
- "66 6212.097890 \n",
- "67 5710.608596 \n",
- "68 5805.377507 \n",
- "69 5427.487599 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_5 \\\n",
- "0 0.020846 \n",
- "1 0.010839 \n",
- "2 0.004030 \n",
- "3 -0.016161 \n",
- "4 0.036635 \n",
- ".. ... \n",
- "65 0.020094 \n",
- "66 -0.017995 \n",
- "67 0.064186 \n",
- "68 0.048656 \n",
- "69 0.110581 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_6 \\\n",
- "0 6048.520615 \n",
- "1 6122.232814 \n",
- "2 6121.457849 \n",
- "3 6182.621856 \n",
- "4 5968.959854 \n",
- ".. ... \n",
- "65 6126.709725 \n",
- "66 6262.068654 \n",
- "67 5874.069955 \n",
- "68 5901.229975 \n",
- "69 5653.479333 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_6 \\\n",
- "0 -0.003566 \n",
- "1 -0.015796 \n",
- "2 -0.015667 \n",
- "3 -0.025816 \n",
- "4 0.009635 \n",
- ".. ... \n",
- "65 -0.004002 \n",
- "66 -0.026184 \n",
- "67 0.037399 \n",
- "68 0.032948 \n",
- "69 0.073548 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_7 \\\n",
- "0 6074.659511 \n",
- "1 6184.281735 \n",
- "2 6210.278943 \n",
- "3 6213.795448 \n",
- "4 6009.615524 \n",
- ".. ... \n",
- "65 6162.581437 \n",
- "66 6179.049182 \n",
- "67 5921.729102 \n",
- "68 5971.856480 \n",
- "69 5880.020669 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_7 \\\n",
- "0 -0.007903 \n",
- "1 -0.026091 \n",
- "2 -0.030404 \n",
- "3 -0.030988 \n",
- "4 0.002889 \n",
- ".. ... \n",
- "65 -0.009881 \n",
- "66 -0.012579 \n",
- "67 0.029589 \n",
- "68 0.021374 \n",
- "69 0.036424 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_8 \\\n",
- "0 6149.594281 \n",
- "1 6199.593162 \n",
- "2 6247.690750 \n",
- "3 6220.357930 \n",
- "4 6028.684646 \n",
- ".. ... \n",
- "65 6100.482692 \n",
- "66 6235.406215 \n",
- "67 5990.038030 \n",
- "68 6054.179537 \n",
- "69 5955.174232 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_8 \\\n",
- "0 -0.020336 \n",
- "1 -0.028632 \n",
- "2 -0.036612 \n",
- "3 -0.032077 \n",
- "4 -0.000275 \n",
- ".. ... \n",
- "65 0.000296 \n",
- "66 -0.021815 \n",
- "67 0.018395 \n",
- "68 0.007884 \n",
- "69 0.024108 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_9 \\\n",
- "0 6175.817312 \n",
- "1 6192.776084 \n",
- "2 6250.071403 \n",
- "3 6228.987740 \n",
- "4 6089.516761 \n",
- ".. ... \n",
- "65 6098.125073 \n",
- "66 6213.565248 \n",
- "67 6126.092314 \n",
- "68 6175.355063 \n",
- "69 6043.195386 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_9 \\\n",
- "0 -0.024687 \n",
- "1 -0.027500 \n",
- "2 -0.037007 \n",
- "3 -0.033509 \n",
- "4 -0.010368 \n",
- ".. ... \n",
- "65 0.000682 \n",
- "66 -0.018235 \n",
- "67 -0.003901 \n",
- "68 -0.011974 \n",
- "69 0.009684 \n",
- "\n",
- " RF_Regressor_train_MSE_after_ablation_10 \\\n",
- "0 6202.436470 \n",
- "1 6202.436470 \n",
- "2 6202.436470 \n",
- "3 6202.436470 \n",
- "4 6202.436470 \n",
- ".. ... \n",
- "65 6136.821625 \n",
- "66 6136.821625 \n",
- "67 6136.821625 \n",
- "68 6136.821625 \n",
- "69 6136.821625 \n",
- "\n",
- " RF_Regressor_train_R_2_after_ablation_10 \\\n",
- "0 -0.029103 \n",
- "1 -0.029103 \n",
- "2 -0.029103 \n",
- "3 -0.029103 \n",
- "4 -0.029103 \n",
- ".. ... \n",
- "65 -0.005659 \n",
- "66 -0.005659 \n",
- "67 -0.005659 \n",
- "68 -0.005659 \n",
- "69 -0.005659 \n",
- "\n",
- " Linear_train_MSE_before_ablation Linear_train_R_2_before_ablation \\\n",
- "0 2888.523636 0.520738 \n",
- "1 2888.523636 0.520738 \n",
- "2 2888.523636 0.520738 \n",
- "3 2888.523636 0.520738 \n",
- "4 2888.523636 0.520738 \n",
- ".. ... ... \n",
- "65 2821.915630 0.537564 \n",
- "66 2821.915630 0.537564 \n",
- "67 2821.915630 0.537564 \n",
- "68 2821.915630 0.537564 \n",
- "69 2821.915630 0.537564 \n",
- "\n",
- " Linear_train_MSE_after_ablation_1 Linear_train_R_2_after_ablation_1 \\\n",
- "0 3761.316620 0.375925 \n",
- "1 3916.706467 0.350143 \n",
- "2 3914.109435 0.350574 \n",
- "3 4024.382264 0.332278 \n",
- "4 3867.089557 0.358376 \n",
- ".. ... ... \n",
- "65 4107.855143 0.326834 \n",
- "66 4124.907264 0.324039 \n",
- "67 4042.670841 0.337516 \n",
- "68 4061.883737 0.334367 \n",
- "69 3838.501816 0.370973 \n",
- "\n",
- " Linear_train_MSE_after_ablation_2 Linear_train_R_2_after_ablation_2 \\\n",
- "0 4957.235173 0.177500 \n",
- "1 5015.669338 0.167804 \n",
- "2 4885.192723 0.189453 \n",
- "3 5102.326251 0.153426 \n",
- "4 4936.004551 0.181022 \n",
- ".. ... ... \n",
- "65 5559.862756 0.088889 \n",
- "66 5934.906752 0.027429 \n",
- "67 5643.649191 0.075158 \n",
- "68 5760.011411 0.056090 \n",
- "69 5478.137514 0.102281 \n",
- "\n",
- " Linear_train_MSE_after_ablation_3 Linear_train_R_2_after_ablation_3 \\\n",
- "0 5736.434644 0.048215 \n",
- "1 5721.361272 0.050716 \n",
- "2 5492.817224 0.088636 \n",
- "3 5740.581038 0.047527 \n",
- "4 5618.567424 0.067772 \n",
- ".. ... ... \n",
- "65 6349.285129 -0.040476 \n",
- "66 6682.422829 -0.095068 \n",
- "67 6612.534967 -0.083616 \n",
- "68 6607.114189 -0.082727 \n",
- "69 6270.632052 -0.027587 \n",
- "\n",
- " Linear_train_MSE_after_ablation_4 Linear_train_R_2_after_ablation_4 \\\n",
- "0 6023.733378 0.000547 \n",
- "1 6139.722264 -0.018698 \n",
- "2 6031.489112 -0.000740 \n",
- "3 6321.322530 -0.048829 \n",
- "4 5961.929743 0.010801 \n",
- ".. ... ... \n",
- "65 6869.438005 -0.125715 \n",
- "66 7204.488112 -0.180621 \n",
- "67 7126.165388 -0.167786 \n",
- "68 7187.319599 -0.177807 \n",
- "69 6728.929011 -0.102690 \n",
- "\n",
- " Linear_train_MSE_after_ablation_5 Linear_train_R_2_after_ablation_5 \\\n",
- "0 6302.387576 -0.045687 \n",
- "1 6341.303427 -0.052144 \n",
- "2 6247.694137 -0.036612 \n",
- "3 6555.449924 -0.087675 \n",
- "4 6114.847766 -0.014571 \n",
- ".. ... ... \n",
- "65 7111.388743 -0.165364 \n",
- "66 7443.348015 -0.219764 \n",
- "67 7249.087498 -0.187930 \n",
- "68 7383.018224 -0.209877 \n",
- "69 7242.790599 -0.186898 \n",
- "\n",
- " Linear_train_MSE_after_ablation_6 Linear_train_R_2_after_ablation_6 \\\n",
- "0 6410.100574 -0.063559 \n",
- "1 6388.554668 -0.059984 \n",
- "2 6325.959184 -0.049598 \n",
- "3 6510.868650 -0.080278 \n",
- "4 6198.656398 -0.028476 \n",
- ".. ... ... \n",
- "65 7315.462544 -0.198807 \n",
- "66 7525.682868 -0.233256 \n",
- "67 7278.281425 -0.192714 \n",
- "68 7452.938431 -0.221335 \n",
- "69 7201.354577 -0.180107 \n",
- "\n",
- " Linear_train_MSE_after_ablation_7 Linear_train_R_2_after_ablation_7 \\\n",
- "0 6404.359728 -0.062606 \n",
- "1 6433.855484 -0.067500 \n",
- "2 6326.214645 -0.049640 \n",
- "3 6390.723824 -0.060344 \n",
- "4 6287.859301 -0.043277 \n",
- ".. ... ... \n",
- "65 7313.503384 -0.198486 \n",
- "66 7552.747816 -0.237691 \n",
- "67 6820.752066 -0.117737 \n",
- "68 7070.721750 -0.158700 \n",
- "69 7055.655190 -0.156231 \n",
- "\n",
- " Linear_train_MSE_after_ablation_8 Linear_train_R_2_after_ablation_8 \\\n",
- "0 6297.330585 -0.044848 \n",
- "1 6443.171782 -0.069046 \n",
- "2 6208.409712 -0.030094 \n",
- "3 6225.389065 -0.032912 \n",
- "4 6274.965297 -0.041137 \n",
- ".. ... ... \n",
- "65 7088.936649 -0.161685 \n",
- "66 7347.797853 -0.204105 \n",
- "67 6559.088545 -0.074857 \n",
- "68 6725.906785 -0.102194 \n",
- "69 6564.300773 -0.075711 \n",
- "\n",
- " Linear_train_MSE_after_ablation_9 Linear_train_R_2_after_ablation_9 \\\n",
- "0 6131.286306 -0.017298 \n",
- "1 6298.161514 -0.044986 \n",
- "2 6127.752193 -0.016712 \n",
- "3 6088.198905 -0.010149 \n",
- "4 6153.972043 -0.021062 \n",
- ".. ... ... \n",
- "65 6596.083346 -0.080920 \n",
- "66 6955.511368 -0.139820 \n",
- "67 6186.218071 -0.013754 \n",
- "68 6256.765405 -0.025315 \n",
- "69 6221.826715 -0.019589 \n",
- "\n",
- " Linear_train_MSE_after_ablation_10 Linear_train_R_2_after_ablation_10 \\\n",
- "0 6027.030120 0.0 \n",
- "1 6027.030120 0.0 \n",
- "2 6027.030120 0.0 \n",
- "3 6027.030120 0.0 \n",
- "4 6027.030120 0.0 \n",
- ".. ... ... \n",
- "65 6102.287573 0.0 \n",
- "66 6102.287573 0.0 \n",
- "67 6102.287573 0.0 \n",
- "68 6102.287573 0.0 \n",
- "69 6102.287573 0.0 \n",
- "\n",
- " XGB_Regressor_train_MSE_before_ablation \\\n",
- "0 0.668153 \n",
- "1 0.668153 \n",
- "2 0.668153 \n",
- "3 0.668153 \n",
- "4 0.668153 \n",
+ "65 0.33 42.0 False 0.0 False \n",
+ "66 0.33 42.0 NaN NaN NaN \n",
+ "67 NaN NaN NaN NaN NaN \n",
+ "68 NaN NaN NaN NaN NaN \n",
+ "69 NaN NaN NaN NaN NaN \n",
+ "\n",
+ " sample_split fit_on model fi train_size test_size \\\n",
+ "0 oob test RF LFI_with_raw_OOB_RF 296 146 \n",
+ "1 NaN NaN RF LFI_with_raw_RF 296 146 \n",
+ "2 inbag NaN RF MDI_RF 296 146 \n",
+ "3 NaN NaN RF TreeSHAP_RF 296 146 \n",
+ "4 NaN NaN RF_plus Kernel_SHAP_RF_plus 296 146 \n",
+ ".. ... ... ... ... ... ... \n",
+ "65 inbag NaN RF MDI_RF 296 146 \n",
+ "66 NaN NaN RF TreeSHAP_RF 296 146 \n",
+ "67 NaN NaN RF_plus Kernel_SHAP_RF_plus 296 146 \n",
+ "68 NaN NaN RF_plus LFI_with_raw_RF_plus 296 146 \n",
+ "69 NaN NaN RF_plus LIME_RF_plus 296 146 \n",
+ "\n",
+ " num_features data_split_seed test_all_mse test_all_r2 sample_train_0 \\\n",
+ "0 10 9 2640.499813 0.535380 274 \n",
+ "1 10 9 2640.499813 0.535380 274 \n",
+ "2 10 9 2640.499813 0.535380 274 \n",
+ "3 10 9 2640.499813 0.535380 274 \n",
+ "4 10 9 2466.857536 0.565934 274 \n",
+ ".. ... ... ... ... ... \n",
+ "65 10 10 3317.655397 0.470632 274 \n",
+ "66 10 10 3317.655397 0.470632 274 \n",
+ "67 10 10 3251.341447 0.481213 274 \n",
+ "68 10 10 3251.341447 0.481213 274 \n",
+ "69 10 10 3251.341447 0.481213 274 \n",
+ "\n",
+ " sample_test_0 sample_train_1 sample_test_1 sample_train_2 \\\n",
+ "0 69 155 30 84 \n",
+ "1 69 155 30 84 \n",
+ "2 69 155 30 84 \n",
+ "3 69 155 30 84 \n",
+ "4 69 155 30 84 \n",
+ ".. ... ... ... ... \n",
+ "65 69 155 30 84 \n",
+ "66 69 155 30 84 \n",
+ "67 69 155 30 84 \n",
+ "68 69 155 30 84 \n",
+ "69 69 155 30 84 \n",
+ "\n",
+ " sample_test_2 sample_train_3 sample_test_3 sample_train_4 \\\n",
+ "0 39 82 2 261 \n",
+ "1 39 82 2 261 \n",
+ "2 39 82 2 261 \n",
+ "3 39 82 2 261 \n",
+ "4 39 82 2 261 \n",
+ ".. ... ... ... ... \n",
+ "65 39 82 2 261 \n",
+ "66 39 82 2 261 \n",
+ "67 39 82 2 261 \n",
+ "68 39 82 2 261 \n",
+ "69 39 82 2 261 \n",
+ "\n",
+ " sample_test_4 sample_train_5 sample_test_5 sample_train_6 \\\n",
+ "0 124 9 10 42 \n",
+ "1 124 9 10 42 \n",
+ "2 124 9 10 42 \n",
+ "3 124 9 10 42 \n",
+ "4 124 9 10 42 \n",
+ ".. ... ... ... ... \n",
+ "65 124 9 10 42 \n",
+ "66 124 9 10 42 \n",
+ "67 124 9 10 42 \n",
+ "68 124 9 10 42 \n",
+ "69 124 9 10 42 \n",
+ "\n",
+ " sample_test_6 sample_train_7 sample_test_7 sample_train_8 \\\n",
+ "0 68 277 51 282 \n",
+ "1 68 277 51 282 \n",
+ "2 68 277 51 282 \n",
+ "3 68 277 51 282 \n",
+ "4 68 277 51 282 \n",
+ ".. ... ... ... ... \n",
+ "65 68 277 51 282 \n",
+ "66 68 277 51 282 \n",
+ "67 68 277 51 282 \n",
+ "68 68 277 51 282 \n",
+ "69 68 277 51 282 \n",
+ "\n",
+ " sample_test_8 sample_train_9 sample_test_9 sample_train_10 \\\n",
+ "0 71 92 77 148 \n",
+ "1 71 92 77 148 \n",
+ "2 71 92 77 148 \n",
+ "3 71 92 77 148 \n",
+ "4 71 92 77 148 \n",
+ ".. ... ... ... ... \n",
+ "65 71 92 77 148 \n",
+ "66 71 92 77 148 \n",
+ "67 71 92 77 148 \n",
+ "68 71 92 77 148 \n",
+ "69 71 92 77 148 \n",
+ "\n",
+ " sample_test_10 sample_train_11 sample_test_11 sample_train_12 \\\n",
+ "0 102 211 80 60 \n",
+ "1 102 211 80 60 \n",
+ "2 102 211 80 60 \n",
+ "3 102 211 80 60 \n",
+ "4 102 211 80 60 \n",
+ ".. ... ... ... ... \n",
+ "65 102 211 80 60 \n",
+ "66 102 211 80 60 \n",
+ "67 102 211 80 60 \n",
+ "68 102 211 80 60 \n",
+ "69 102 211 80 60 \n",
+ "\n",
+ " sample_test_12 sample_train_13 sample_test_13 sample_train_14 \\\n",
+ "0 76 218 142 262 \n",
+ "1 76 218 142 262 \n",
+ "2 76 218 142 262 \n",
+ "3 76 218 142 262 \n",
+ "4 76 218 142 262 \n",
+ ".. ... ... ... ... \n",
+ "65 76 218 142 262 \n",
+ "66 76 218 142 262 \n",
+ "67 76 218 142 262 \n",
+ "68 76 218 142 262 \n",
+ "69 76 218 142 262 \n",
+ "\n",
+ " sample_test_14 sample_train_15 sample_test_15 sample_train_16 \\\n",
+ "0 127 46 95 45 \n",
+ "1 127 46 95 45 \n",
+ "2 127 46 95 45 \n",
+ "3 127 46 95 45 \n",
+ "4 127 46 95 45 \n",
+ ".. ... ... ... ... \n",
+ "65 127 46 95 45 \n",
+ "66 127 46 95 45 \n",
+ "67 127 46 95 45 \n",
+ "68 127 46 95 45 \n",
+ "69 127 46 95 45 \n",
+ "\n",
+ " sample_test_16 sample_train_17 sample_test_17 sample_train_18 \\\n",
+ "0 70 236 93 228 \n",
+ "1 70 236 93 228 \n",
+ "2 70 236 93 228 \n",
+ "3 70 236 93 228 \n",
+ "4 70 236 93 228 \n",
+ ".. ... ... ... ... \n",
+ "65 70 236 93 228 \n",
+ "66 70 236 93 228 \n",
+ "67 70 236 93 228 \n",
+ "68 70 236 93 228 \n",
+ "69 70 236 93 228 \n",
+ "\n",
+ " sample_test_18 sample_train_19 sample_test_19 sample_train_20 \\\n",
+ "0 67 132 0 143 \n",
+ "1 67 132 0 143 \n",
+ "2 67 132 0 143 \n",
+ "3 67 132 0 143 \n",
+ "4 67 132 0 143 \n",
+ ".. ... ... ... ... \n",
+ "65 67 132 0 143 \n",
+ "66 67 132 0 143 \n",
+ "67 67 132 0 143 \n",
+ "68 67 132 0 143 \n",
+ "69 67 132 0 143 \n",
+ "\n",
+ " sample_test_20 sample_train_21 sample_test_21 sample_train_22 \\\n",
+ "0 105 167 82 152 \n",
+ "1 105 167 82 152 \n",
+ "2 105 167 82 152 \n",
+ "3 105 167 82 152 \n",
+ "4 105 167 82 152 \n",
+ ".. ... ... ... ... \n",
+ "65 105 167 82 152 \n",
+ "66 105 167 82 152 \n",
+ "67 105 167 82 152 \n",
+ "68 105 167 82 152 \n",
+ "69 105 167 82 152 \n",
+ "\n",
+ " sample_test_22 sample_train_23 sample_test_23 sample_train_24 \\\n",
+ "0 136 93 40 113 \n",
+ "1 136 93 40 113 \n",
+ "2 136 93 40 113 \n",
+ "3 136 93 40 113 \n",
+ "4 136 93 40 113 \n",
+ ".. ... ... ... ... \n",
+ "65 136 93 40 113 \n",
+ "66 136 93 40 113 \n",
+ "67 136 93 40 113 \n",
+ "68 136 93 40 113 \n",
+ "69 136 93 40 113 \n",
+ "\n",
+ " sample_test_24 sample_train_25 sample_test_25 sample_train_26 \\\n",
+ "0 54 5 28 238 \n",
+ "1 54 5 28 238 \n",
+ "2 54 5 28 238 \n",
+ "3 54 5 28 238 \n",
+ "4 54 5 28 238 \n",
+ ".. ... ... ... ... \n",
+ "65 54 5 28 238 \n",
+ "66 54 5 28 238 \n",
+ "67 54 5 28 238 \n",
+ "68 54 5 28 238 \n",
+ "69 54 5 28 238 \n",
+ "\n",
+ " sample_test_26 sample_train_27 sample_test_27 sample_train_28 \\\n",
+ "0 74 251 119 170 \n",
+ "1 74 251 119 170 \n",
+ "2 74 251 119 170 \n",
+ "3 74 251 119 170 \n",
+ "4 74 251 119 170 \n",
+ ".. ... ... ... ... \n",
+ "65 74 251 119 170 \n",
+ "66 74 251 119 170 \n",
+ "67 74 251 119 170 \n",
+ "68 74 251 119 170 \n",
+ "69 74 251 119 170 \n",
+ "\n",
+ " sample_test_28 sample_train_29 sample_test_29 sample_train_30 \\\n",
+ "0 18 186 9 193 \n",
+ "1 18 186 9 193 \n",
+ "2 18 186 9 193 \n",
+ "3 18 186 9 193 \n",
+ "4 18 186 9 193 \n",
+ ".. ... ... ... ... \n",
+ "65 18 186 9 193 \n",
+ "66 18 186 9 193 \n",
+ "67 18 186 9 193 \n",
+ "68 18 186 9 193 \n",
+ "69 18 186 9 193 \n",
+ "\n",
+ " sample_test_30 sample_train_31 sample_test_31 sample_train_32 \\\n",
+ "0 58 33 99 222 \n",
+ "1 58 33 99 222 \n",
+ "2 58 33 99 222 \n",
+ "3 58 33 99 222 \n",
+ "4 58 33 99 222 \n",
+ ".. ... ... ... ... \n",
+ "65 58 33 99 222 \n",
+ "66 58 33 99 222 \n",
+ "67 58 33 99 222 \n",
+ "68 58 33 99 222 \n",
+ "69 58 33 99 222 \n",
+ "\n",
+ " sample_test_32 sample_train_33 sample_test_33 sample_train_34 \\\n",
+ "0 73 216 97 197 \n",
+ "1 73 216 97 197 \n",
+ "2 73 216 97 197 \n",
+ "3 73 216 97 197 \n",
+ "4 73 216 97 197 \n",
+ ".. ... ... ... ... \n",
+ "65 73 216 97 197 \n",
+ "66 73 216 97 197 \n",
+ "67 73 216 97 197 \n",
+ "68 73 216 97 197 \n",
+ "69 73 216 97 197 \n",
+ "\n",
+ " sample_test_34 sample_train_35 sample_test_35 sample_train_36 \\\n",
+ "0 128 73 122 182 \n",
+ "1 128 73 122 182 \n",
+ "2 128 73 122 182 \n",
+ "3 128 73 122 182 \n",
+ "4 128 73 122 182 \n",
+ ".. ... ... ... ... \n",
+ "65 128 73 122 182 \n",
+ "66 128 73 122 182 \n",
+ "67 128 73 122 182 \n",
+ "68 128 73 122 182 \n",
+ "69 128 73 122 182 \n",
+ "\n",
+ " sample_test_36 sample_train_37 sample_test_37 sample_train_38 \\\n",
+ "0 55 119 90 285 \n",
+ "1 55 119 90 285 \n",
+ "2 55 119 90 285 \n",
+ "3 55 119 90 285 \n",
+ "4 55 119 90 285 \n",
+ ".. ... ... ... ... \n",
+ "65 55 119 90 285 \n",
+ "66 55 119 90 285 \n",
+ "67 55 119 90 285 \n",
+ "68 55 119 90 285 \n",
+ "69 55 119 90 285 \n",
+ "\n",
+ " sample_test_38 sample_train_39 sample_test_39 sample_train_40 \\\n",
+ "0 129 202 79 204 \n",
+ "1 129 202 79 204 \n",
+ "2 129 202 79 204 \n",
+ "3 129 202 79 204 \n",
+ "4 129 202 79 204 \n",
+ ".. ... ... ... ... \n",
+ "65 129 202 79 204 \n",
+ "66 129 202 79 204 \n",
+ "67 129 202 79 204 \n",
+ "68 129 202 79 204 \n",
+ "69 129 202 79 204 \n",
+ "\n",
+ " sample_test_40 sample_train_41 sample_test_41 sample_train_42 \\\n",
+ "0 4 179 87 177 \n",
+ "1 4 179 87 177 \n",
+ "2 4 179 87 177 \n",
+ "3 4 179 87 177 \n",
+ "4 4 179 87 177 \n",
+ ".. ... ... ... ... \n",
+ "65 4 179 87 177 \n",
+ "66 4 179 87 177 \n",
+ "67 4 179 87 177 \n",
+ "68 4 179 87 177 \n",
+ "69 4 179 87 177 \n",
+ "\n",
+ " sample_test_42 sample_train_43 sample_test_43 sample_train_44 \\\n",
+ "0 83 111 115 59 \n",
+ "1 83 111 115 59 \n",
+ "2 83 111 115 59 \n",
+ "3 83 111 115 59 \n",
+ "4 83 111 115 59 \n",
+ ".. ... ... ... ... \n",
+ "65 83 111 115 59 \n",
+ "66 83 111 115 59 \n",
+ "67 83 111 115 59 \n",
+ "68 83 111 115 59 \n",
+ "69 83 111 115 59 \n",
+ "\n",
+ " sample_test_44 sample_train_45 sample_test_45 sample_train_46 \\\n",
+ "0 81 226 72 25 \n",
+ "1 81 226 72 25 \n",
+ "2 81 226 72 25 \n",
+ "3 81 226 72 25 \n",
+ "4 81 226 72 25 \n",
+ ".. ... ... ... ... \n",
+ "65 81 226 72 25 \n",
+ "66 81 226 72 25 \n",
+ "67 81 226 72 25 \n",
+ "68 81 226 72 25 \n",
+ "69 81 226 72 25 \n",
+ "\n",
+ " sample_test_46 sample_train_47 sample_test_47 sample_train_48 \\\n",
+ "0 144 77 78 6 \n",
+ "1 144 77 78 6 \n",
+ "2 144 77 78 6 \n",
+ "3 144 77 78 6 \n",
+ "4 144 77 78 6 \n",
+ ".. ... ... ... ... \n",
+ "65 144 77 78 6 \n",
+ "66 144 77 78 6 \n",
+ "67 144 77 78 6 \n",
+ "68 144 77 78 6 \n",
+ "69 144 77 78 6 \n",
+ "\n",
+ " sample_test_48 sample_train_49 sample_test_49 sample_train_50 \\\n",
+ "0 126 175 132 164 \n",
+ "1 126 175 132 164 \n",
+ "2 126 175 132 164 \n",
+ "3 126 175 132 164 \n",
+ "4 126 175 132 164 \n",
+ ".. ... ... ... ... \n",
+ "65 126 175 132 164 \n",
+ "66 126 175 132 164 \n",
+ "67 126 175 132 164 \n",
+ "68 126 175 132 164 \n",
+ "69 126 175 132 164 \n",
+ "\n",
+ " sample_test_50 sample_train_51 sample_test_51 sample_train_52 \\\n",
+ "0 106 140 75 30 \n",
+ "1 106 140 75 30 \n",
+ "2 106 140 75 30 \n",
+ "3 106 140 75 30 \n",
+ "4 106 140 75 30 \n",
+ ".. ... ... ... ... \n",
+ "65 106 140 75 30 \n",
+ "66 106 140 75 30 \n",
+ "67 106 140 75 30 \n",
+ "68 106 140 75 30 \n",
+ "69 106 140 75 30 \n",
+ "\n",
+ " sample_test_52 sample_train_53 sample_test_53 sample_train_54 \\\n",
+ "0 61 22 143 245 \n",
+ "1 61 22 143 245 \n",
+ "2 61 22 143 245 \n",
+ "3 61 22 143 245 \n",
+ "4 61 22 143 245 \n",
+ ".. ... ... ... ... \n",
+ "65 61 22 143 245 \n",
+ "66 61 22 143 245 \n",
+ "67 61 22 143 245 \n",
+ "68 61 22 143 245 \n",
+ "69 61 22 143 245 \n",
+ "\n",
+ " sample_test_54 sample_train_55 sample_test_55 sample_train_56 \\\n",
+ "0 131 24 123 56 \n",
+ "1 131 24 123 56 \n",
+ "2 131 24 123 56 \n",
+ "3 131 24 123 56 \n",
+ "4 131 24 123 56 \n",
+ ".. ... ... ... ... \n",
+ "65 131 24 123 56 \n",
+ "66 131 24 123 56 \n",
+ "67 131 24 123 56 \n",
+ "68 131 24 123 56 \n",
+ "69 131 24 123 56 \n",
+ "\n",
+ " sample_test_56 sample_train_57 sample_test_57 sample_train_58 \\\n",
+ "0 89 144 33 124 \n",
+ "1 89 144 33 124 \n",
+ "2 89 144 33 124 \n",
+ "3 89 144 33 124 \n",
+ "4 89 144 33 124 \n",
+ ".. ... ... ... ... \n",
+ "65 89 144 33 124 \n",
+ "66 89 144 33 124 \n",
+ "67 89 144 33 124 \n",
+ "68 89 144 33 124 \n",
+ "69 89 144 33 124 \n",
+ "\n",
+ " sample_test_58 sample_train_59 sample_test_59 sample_train_60 \\\n",
+ "0 133 97 14 63 \n",
+ "1 133 97 14 63 \n",
+ "2 133 97 14 63 \n",
+ "3 133 97 14 63 \n",
+ "4 133 97 14 63 \n",
+ ".. ... ... ... ... \n",
+ "65 133 97 14 63 \n",
+ "66 133 97 14 63 \n",
+ "67 133 97 14 63 \n",
+ "68 133 97 14 63 \n",
+ "69 133 97 14 63 \n",
+ "\n",
+ " sample_test_60 sample_train_61 sample_test_61 sample_train_62 \\\n",
+ "0 88 17 140 215 \n",
+ "1 88 17 140 215 \n",
+ "2 88 17 140 215 \n",
+ "3 88 17 140 215 \n",
+ "4 88 17 140 215 \n",
+ ".. ... ... ... ... \n",
+ "65 88 17 140 215 \n",
+ "66 88 17 140 215 \n",
+ "67 88 17 140 215 \n",
+ "68 88 17 140 215 \n",
+ "69 88 17 140 215 \n",
+ "\n",
+ " sample_test_62 sample_train_63 sample_test_63 sample_train_64 \\\n",
+ "0 11 219 13 183 \n",
+ "1 11 219 13 183 \n",
+ "2 11 219 13 183 \n",
+ "3 11 219 13 183 \n",
+ "4 11 219 13 183 \n",
+ ".. ... ... ... ... \n",
+ "65 11 219 13 183 \n",
+ "66 11 219 13 183 \n",
+ "67 11 219 13 183 \n",
+ "68 11 219 13 183 \n",
+ "69 11 219 13 183 \n",
+ "\n",
+ " sample_test_64 sample_train_65 sample_test_65 sample_train_66 \\\n",
+ "0 15 114 139 76 \n",
+ "1 15 114 139 76 \n",
+ "2 15 114 139 76 \n",
+ "3 15 114 139 76 \n",
+ "4 15 114 139 76 \n",
+ ".. ... ... ... ... \n",
+ "65 15 114 139 76 \n",
+ "66 15 114 139 76 \n",
+ "67 15 114 139 76 \n",
+ "68 15 114 139 76 \n",
+ "69 15 114 139 76 \n",
+ "\n",
+ " sample_test_66 sample_train_67 sample_test_67 sample_train_68 \\\n",
+ "0 64 284 19 66 \n",
+ "1 64 284 19 66 \n",
+ "2 64 284 19 66 \n",
+ "3 64 284 19 66 \n",
+ "4 64 284 19 66 \n",
+ ".. ... ... ... ... \n",
+ "65 64 284 19 66 \n",
+ "66 64 284 19 66 \n",
+ "67 64 284 19 66 \n",
+ "68 64 284 19 66 \n",
+ "69 64 284 19 66 \n",
+ "\n",
+ " sample_test_68 sample_train_69 sample_test_69 sample_train_70 \\\n",
+ "0 44 178 35 154 \n",
+ "1 44 178 35 154 \n",
+ "2 44 178 35 154 \n",
+ "3 44 178 35 154 \n",
+ "4 44 178 35 154 \n",
+ ".. ... ... ... ... \n",
+ "65 44 178 35 154 \n",
+ "66 44 178 35 154 \n",
+ "67 44 178 35 154 \n",
+ "68 44 178 35 154 \n",
+ "69 44 178 35 154 \n",
+ "\n",
+ " sample_test_70 sample_train_71 sample_test_71 sample_train_72 \\\n",
+ "0 56 75 6 19 \n",
+ "1 56 75 6 19 \n",
+ "2 56 75 6 19 \n",
+ "3 56 75 6 19 \n",
+ "4 56 75 6 19 \n",
+ ".. ... ... ... ... \n",
+ "65 56 75 6 19 \n",
+ "66 56 75 6 19 \n",
+ "67 56 75 6 19 \n",
+ "68 56 75 6 19 \n",
+ "69 56 75 6 19 \n",
+ "\n",
+ " sample_test_72 sample_train_73 sample_test_73 sample_train_74 \\\n",
+ "0 107 108 12 79 \n",
+ "1 107 108 12 79 \n",
+ "2 107 108 12 79 \n",
+ "3 107 108 12 79 \n",
+ "4 107 108 12 79 \n",
+ ".. ... ... ... ... \n",
+ "65 107 108 12 79 \n",
+ "66 107 108 12 79 \n",
+ "67 107 108 12 79 \n",
+ "68 107 108 12 79 \n",
+ "69 107 108 12 79 \n",
+ "\n",
+ " sample_test_74 sample_train_75 sample_test_75 sample_train_76 \\\n",
+ "0 113 118 141 72 \n",
+ "1 113 118 141 72 \n",
+ "2 113 118 141 72 \n",
+ "3 113 118 141 72 \n",
+ "4 113 118 141 72 \n",
+ ".. ... ... ... ... \n",
+ "65 113 118 141 72 \n",
+ "66 113 118 141 72 \n",
+ "67 113 118 141 72 \n",
+ "68 113 118 141 72 \n",
+ "69 113 118 141 72 \n",
+ "\n",
+ " sample_test_76 sample_train_77 sample_test_77 sample_train_78 \\\n",
+ "0 49 15 25 10 \n",
+ "1 49 15 25 10 \n",
+ "2 49 15 25 10 \n",
+ "3 49 15 25 10 \n",
+ "4 49 15 25 10 \n",
+ ".. ... ... ... ... \n",
+ "65 49 15 25 10 \n",
+ "66 49 15 25 10 \n",
+ "67 49 15 25 10 \n",
+ "68 49 15 25 10 \n",
+ "69 49 15 25 10 \n",
+ "\n",
+ " sample_test_78 sample_train_79 sample_test_79 sample_train_80 \\\n",
+ "0 41 101 38 68 \n",
+ "1 41 101 38 68 \n",
+ "2 41 101 38 68 \n",
+ "3 41 101 38 68 \n",
+ "4 41 101 38 68 \n",
+ ".. ... ... ... ... \n",
+ "65 41 101 38 68 \n",
+ "66 41 101 38 68 \n",
+ "67 41 101 38 68 \n",
+ "68 41 101 38 68 \n",
+ "69 41 101 38 68 \n",
+ "\n",
+ " sample_test_80 sample_train_81 sample_test_81 sample_train_82 \\\n",
+ "0 130 125 42 37 \n",
+ "1 130 125 42 37 \n",
+ "2 130 125 42 37 \n",
+ "3 130 125 42 37 \n",
+ "4 130 125 42 37 \n",
+ ".. ... ... ... ... \n",
+ "65 130 125 42 37 \n",
+ "66 130 125 42 37 \n",
+ "67 130 125 42 37 \n",
+ "68 130 125 42 37 \n",
+ "69 130 125 42 37 \n",
+ "\n",
+ " sample_test_82 sample_train_83 sample_test_83 sample_train_84 \\\n",
+ "0 8 16 101 293 \n",
+ "1 8 16 101 293 \n",
+ "2 8 16 101 293 \n",
+ "3 8 16 101 293 \n",
+ "4 8 16 101 293 \n",
+ ".. ... ... ... ... \n",
+ "65 8 16 101 293 \n",
+ "66 8 16 101 293 \n",
+ "67 8 16 101 293 \n",
+ "68 8 16 101 293 \n",
+ "69 8 16 101 293 \n",
+ "\n",
+ " sample_test_84 sample_train_85 sample_test_85 sample_train_86 \\\n",
+ "0 125 139 1 266 \n",
+ "1 125 139 1 266 \n",
+ "2 125 139 1 266 \n",
+ "3 125 139 1 266 \n",
+ "4 125 139 1 266 \n",
+ ".. ... ... ... ... \n",
+ "65 125 139 1 266 \n",
+ "66 125 139 1 266 \n",
+ "67 125 139 1 266 \n",
+ "68 125 139 1 266 \n",
+ "69 125 139 1 266 \n",
+ "\n",
+ " sample_test_86 sample_train_87 sample_test_87 sample_train_88 \\\n",
+ "0 137 67 65 90 \n",
+ "1 137 67 65 90 \n",
+ "2 137 67 65 90 \n",
+ "3 137 67 65 90 \n",
+ "4 137 67 65 90 \n",
+ ".. ... ... ... ... \n",
+ "65 137 67 65 90 \n",
+ "66 137 67 65 90 \n",
+ "67 137 67 65 90 \n",
+ "68 137 67 65 90 \n",
+ "69 137 67 65 90 \n",
+ "\n",
+ " sample_test_88 sample_train_89 sample_test_89 sample_train_90 \\\n",
+ "0 22 69 85 288 \n",
+ "1 22 69 85 288 \n",
+ "2 22 69 85 288 \n",
+ "3 22 69 85 288 \n",
+ "4 22 69 85 288 \n",
+ ".. ... ... ... ... \n",
+ "65 22 69 85 288 \n",
+ "66 22 69 85 288 \n",
+ "67 22 69 85 288 \n",
+ "68 22 69 85 288 \n",
+ "69 22 69 85 288 \n",
+ "\n",
+ " sample_test_90 sample_train_91 sample_test_91 sample_train_92 \\\n",
+ "0 46 165 103 126 \n",
+ "1 46 165 103 126 \n",
+ "2 46 165 103 126 \n",
+ "3 46 165 103 126 \n",
+ "4 46 165 103 126 \n",
+ ".. ... ... ... ... \n",
+ "65 46 165 103 126 \n",
+ "66 46 165 103 126 \n",
+ "67 46 165 103 126 \n",
+ "68 46 165 103 126 \n",
+ "69 46 165 103 126 \n",
+ "\n",
+ " sample_test_92 sample_train_93 sample_test_93 sample_train_94 \\\n",
+ "0 145 221 111 173 \n",
+ "1 145 221 111 173 \n",
+ "2 145 221 111 173 \n",
+ "3 145 221 111 173 \n",
+ "4 145 221 111 173 \n",
+ ".. ... ... ... ... \n",
+ "65 145 221 111 173 \n",
+ "66 145 221 111 173 \n",
+ "67 145 221 111 173 \n",
+ "68 145 221 111 173 \n",
+ "69 145 221 111 173 \n",
+ "\n",
+ " sample_test_94 sample_train_95 sample_test_95 sample_train_96 \\\n",
+ "0 100 18 57 172 \n",
+ "1 100 18 57 172 \n",
+ "2 100 18 57 172 \n",
+ "3 100 18 57 172 \n",
+ "4 100 18 57 172 \n",
+ ".. ... ... ... ... \n",
+ "65 100 18 57 172 \n",
+ "66 100 18 57 172 \n",
+ "67 100 18 57 172 \n",
+ "68 100 18 57 172 \n",
+ "69 100 18 57 172 \n",
+ "\n",
+ " sample_test_96 sample_train_97 sample_test_97 sample_train_98 \\\n",
+ "0 53 96 109 146 \n",
+ "1 53 96 109 146 \n",
+ "2 53 96 109 146 \n",
+ "3 53 96 109 146 \n",
+ "4 53 96 109 146 \n",
+ ".. ... ... ... ... \n",
+ "65 53 96 109 146 \n",
+ "66 53 96 109 146 \n",
+ "67 53 96 109 146 \n",
+ "68 53 96 109 146 \n",
+ "69 53 96 109 146 \n",
+ "\n",
+ " sample_test_98 sample_train_99 sample_test_99 ablation_seed_0 \\\n",
+ "0 24 86 17 545 \n",
+ "1 24 86 17 545 \n",
+ "2 24 86 17 545 \n",
+ "3 24 86 17 545 \n",
+ "4 24 86 17 8534 \n",
+ ".. ... ... ... ... \n",
+ "65 24 86 17 3650 \n",
+ "66 24 86 17 3650 \n",
+ "67 24 86 17 8563 \n",
+ "68 24 86 17 8563 \n",
+ "69 24 86 17 8563 \n",
+ "\n",
+ " fi_time RF_Regressor_train_subset_MSE_before_ablation \\\n",
+ "0 8.739464 1437.058926 \n",
+ "1 9.849160 1437.058926 \n",
+ "2 3.896490 1437.058926 \n",
+ "3 0.353197 1437.058926 \n",
+ "4 134.209250 1437.058926 \n",
+ ".. ... ... \n",
+ "65 4.258376 1438.855135 \n",
+ "66 0.352780 1438.855135 \n",
+ "67 151.621587 1438.855135 \n",
+ "68 2.607143 1438.855135 \n",
+ "69 315.562780 1438.855135 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_before_ablation \\\n",
+ "0 0.740320 \n",
+ "1 0.740320 \n",
+ "2 0.740320 \n",
+ "3 0.740320 \n",
+ "4 0.740320 \n",
+ ".. ... \n",
+ "65 0.742201 \n",
+ "66 0.742201 \n",
+ "67 0.742201 \n",
+ "68 0.742201 \n",
+ "69 0.742201 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_1 \\\n",
+ "0 2450.453723 \n",
+ "1 2554.479820 \n",
+ "2 2900.469581 \n",
+ "3 2993.318633 \n",
+ "4 2593.668426 \n",
+ ".. ... \n",
+ "65 2678.898633 \n",
+ "66 2782.889805 \n",
+ "67 2749.901178 \n",
+ "68 2572.532707 \n",
+ "69 2720.135924 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_1 \\\n",
+ "0 0.557198 \n",
+ "1 0.538400 \n",
+ "2 0.475879 \n",
+ "3 0.459101 \n",
+ "4 0.531318 \n",
+ ".. ... \n",
+ "65 0.520023 \n",
+ "66 0.501391 \n",
+ "67 0.507302 \n",
+ "68 0.539081 \n",
+ "69 0.512635 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_2 \\\n",
+ "0 3708.135984 \n",
+ "1 3776.859055 \n",
+ "2 4039.948602 \n",
+ "3 4185.208775 \n",
+ "4 3915.160119 \n",
+ ".. ... \n",
+ "65 4165.208912 \n",
+ "66 4366.241529 \n",
+ "67 4346.155760 \n",
+ "68 4175.221232 \n",
+ "69 3782.575791 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_2 \\\n",
+ "0 0.329932 \n",
+ "1 0.317513 \n",
+ "2 0.269972 \n",
+ "3 0.243723 \n",
+ "4 0.292522 \n",
+ ".. ... \n",
+ "65 0.253722 \n",
+ "66 0.217703 \n",
+ "67 0.221302 \n",
+ "68 0.251928 \n",
+ "69 0.322278 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_3 \\\n",
+ "0 4626.637491 \n",
+ "1 4555.990329 \n",
+ "2 4745.392296 \n",
+ "3 4928.490103 \n",
+ "4 4678.388000 \n",
+ ".. ... \n",
+ "65 4813.668323 \n",
+ "66 5070.550880 \n",
+ "67 5105.225598 \n",
+ "68 4881.927373 \n",
+ "69 4604.837368 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_3 \\\n",
+ "0 0.163956 \n",
+ "1 0.176722 \n",
+ "2 0.142497 \n",
+ "3 0.109411 \n",
+ "4 0.154605 \n",
+ ".. ... \n",
+ "65 0.137538 \n",
+ "66 0.091512 \n",
+ "67 0.085300 \n",
+ "68 0.125308 \n",
+ "69 0.174954 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_4 \\\n",
+ "0 4988.459417 \n",
+ "1 5094.477192 \n",
+ "2 5121.591713 \n",
+ "3 5342.614052 \n",
+ "4 5028.409569 \n",
+ ".. ... \n",
+ "65 5176.160990 \n",
+ "66 5466.312513 \n",
+ "67 5126.939895 \n",
+ "68 5173.172791 \n",
+ "69 5200.792476 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_4 \\\n",
+ "0 0.098574 \n",
+ "1 0.079417 \n",
+ "2 0.074517 \n",
+ "3 0.034578 \n",
+ "4 0.091355 \n",
+ ".. ... \n",
+ "65 0.072590 \n",
+ "66 0.020604 \n",
+ "67 0.081409 \n",
+ "68 0.073126 \n",
+ "69 0.068177 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_5 \\\n",
+ "0 5232.901749 \n",
+ "1 5291.593590 \n",
+ "2 5396.791508 \n",
+ "3 5522.340805 \n",
+ "4 5173.721429 \n",
+ ".. ... \n",
+ "65 5445.473321 \n",
+ "66 5611.598042 \n",
+ "67 5288.691321 \n",
+ "68 5217.655724 \n",
+ "69 5225.942001 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_5 \\\n",
+ "0 0.054403 \n",
+ "1 0.043797 \n",
+ "2 0.024788 \n",
+ "3 0.002101 \n",
+ "4 0.065097 \n",
+ ".. ... \n",
+ "65 0.024338 \n",
+ "66 -0.005427 \n",
+ "67 0.052428 \n",
+ "68 0.065156 \n",
+ "69 0.063671 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_6 \\\n",
+ "0 5437.430361 \n",
+ "1 5426.338268 \n",
+ "2 5433.771000 \n",
+ "3 5482.240393 \n",
+ "4 5309.990518 \n",
+ ".. ... \n",
+ "65 5445.779737 \n",
+ "66 5618.506871 \n",
+ "67 5392.616386 \n",
+ "68 5405.903732 \n",
+ "69 5344.152735 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_6 \\\n",
+ "0 0.017444 \n",
+ "1 0.019449 \n",
+ "2 0.018105 \n",
+ "3 0.009347 \n",
+ "4 0.040473 \n",
+ ".. ... \n",
+ "65 0.024283 \n",
+ "66 -0.006665 \n",
+ "67 0.033808 \n",
+ "68 0.031427 \n",
+ "69 0.042491 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_7 \\\n",
+ "0 5421.293849 \n",
+ "1 5451.723835 \n",
+ "2 5483.243120 \n",
+ "3 5577.046415 \n",
+ "4 5380.005758 \n",
+ ".. ... \n",
+ "65 5590.734303 \n",
+ "66 5654.910570 \n",
+ "67 5490.010870 \n",
+ "68 5481.723324 \n",
+ "69 5359.167068 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_7 \\\n",
+ "0 0.020360 \n",
+ "1 0.014861 \n",
+ "2 0.009166 \n",
+ "3 -0.007785 \n",
+ "4 0.027821 \n",
+ ".. ... \n",
+ "65 -0.001689 \n",
+ "66 -0.013187 \n",
+ "67 0.016358 \n",
+ "68 0.017843 \n",
+ "69 0.039801 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_8 \\\n",
+ "0 5443.743634 \n",
+ "1 5477.274281 \n",
+ "2 5426.787503 \n",
+ "3 5602.663206 \n",
+ "4 5537.554053 \n",
+ ".. ... \n",
+ "65 5562.477277 \n",
+ "66 5619.409496 \n",
+ "67 5642.366051 \n",
+ "68 5538.033353 \n",
+ "69 5475.811021 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_8 \\\n",
+ "0 0.016303 \n",
+ "1 0.010244 \n",
+ "2 0.019367 \n",
+ "3 -0.012414 \n",
+ "4 -0.000648 \n",
+ ".. ... \n",
+ "65 0.003374 \n",
+ "66 -0.006826 \n",
+ "67 -0.010939 \n",
+ "68 0.007754 \n",
+ "69 0.018902 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_9 \\\n",
+ "0 5494.702450 \n",
+ "1 5514.501633 \n",
+ "2 5506.799767 \n",
+ "3 5644.869200 \n",
+ "4 5547.269238 \n",
+ ".. ... \n",
+ "65 5710.567724 \n",
+ "66 5634.681385 \n",
+ "67 5642.172216 \n",
+ "68 5649.927048 \n",
+ "69 5618.005145 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_9 \\\n",
+ "0 0.007095 \n",
+ "1 0.003517 \n",
+ "2 0.004909 \n",
+ "3 -0.020040 \n",
+ "4 -0.002404 \n",
+ ".. ... \n",
+ "65 -0.023159 \n",
+ "66 -0.009563 \n",
+ "67 -0.010905 \n",
+ "68 -0.012294 \n",
+ "69 -0.006575 \n",
+ "\n",
+ " RF_Regressor_train_subset_MSE_after_ablation_10 \\\n",
+ "0 5539.523521 \n",
+ "1 5539.523521 \n",
+ "2 5539.523521 \n",
+ "3 5539.523521 \n",
+ "4 5539.523521 \n",
+ ".. ... \n",
+ "65 5687.565590 \n",
+ "66 5687.565590 \n",
+ "67 5687.565590 \n",
+ "68 5687.565590 \n",
+ "69 5687.565590 \n",
+ "\n",
+ " RF_Regressor_train_subset_R_2_after_ablation_10 \\\n",
+ "0 -0.001004 \n",
+ "1 -0.001004 \n",
+ "2 -0.001004 \n",
+ "3 -0.001004 \n",
+ "4 -0.001004 \n",
+ ".. ... \n",
+ "65 -0.019038 \n",
+ "66 -0.019038 \n",
+ "67 -0.019038 \n",
+ "68 -0.019038 \n",
+ "69 -0.019038 \n",
+ "\n",
+ " Linear_train_subset_MSE_before_ablation \\\n",
+ "0 2751.227274 \n",
+ "1 2751.227274 \n",
+ "2 2751.227274 \n",
+ "3 2751.227274 \n",
+ "4 2751.227274 \n",
".. ... \n",
- "65 0.760518 \n",
- "66 0.760518 \n",
- "67 0.760518 \n",
- "68 0.760518 \n",
- "69 0.760518 \n",
- "\n",
- " XGB_Regressor_train_R_2_before_ablation \\\n",
- "0 0.999889 \n",
- "1 0.999889 \n",
- "2 0.999889 \n",
- "3 0.999889 \n",
- "4 0.999889 \n",
+ "65 2738.215621 \n",
+ "66 2738.215621 \n",
+ "67 2738.215621 \n",
+ "68 2738.215621 \n",
+ "69 2738.215621 \n",
+ "\n",
+ " Linear_train_subset_R_2_before_ablation \\\n",
+ "0 0.502847 \n",
+ "1 0.502847 \n",
+ "2 0.502847 \n",
+ "3 0.502847 \n",
+ "4 0.502847 \n",
".. ... \n",
- "65 0.999875 \n",
- "66 0.999875 \n",
- "67 0.999875 \n",
- "68 0.999875 \n",
- "69 0.999875 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_1 \\\n",
- "0 1216.244402 \n",
- "1 1208.211458 \n",
- "2 1213.928121 \n",
- "3 1110.645464 \n",
- "4 1227.836013 \n",
+ "65 0.509396 \n",
+ "66 0.509396 \n",
+ "67 0.509396 \n",
+ "68 0.509396 \n",
+ "69 0.509396 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_1 \\\n",
+ "0 4010.135272 \n",
+ "1 4077.155488 \n",
+ "2 4417.646065 \n",
+ "3 4702.534726 \n",
+ "4 4131.487251 \n",
".. ... \n",
- "65 1763.906154 \n",
- "66 1782.617426 \n",
- "67 1830.868812 \n",
- "68 1549.952598 \n",
- "69 1461.549087 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_1 \\\n",
- "0 0.798202 \n",
- "1 0.799535 \n",
- "2 0.798586 \n",
- "3 0.815723 \n",
- "4 0.796278 \n",
+ "65 3827.443185 \n",
+ "66 3923.613699 \n",
+ "67 3659.801644 \n",
+ "68 3827.975616 \n",
+ "69 3798.702668 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_1 \\\n",
+ "0 0.275360 \n",
+ "1 0.263249 \n",
+ "2 0.201721 \n",
+ "3 0.150241 \n",
+ "4 0.253431 \n",
".. ... \n",
- "65 0.710943 \n",
- "66 0.707877 \n",
- "67 0.699970 \n",
- "68 0.746005 \n",
- "69 0.760492 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_2 \\\n",
- "0 2651.509022 \n",
- "1 2624.721798 \n",
- "2 2602.100460 \n",
- "3 2856.413683 \n",
- "4 2655.454874 \n",
+ "65 0.314239 \n",
+ "66 0.297008 \n",
+ "67 0.344275 \n",
+ "68 0.314144 \n",
+ "69 0.319389 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_2 \\\n",
+ "0 5532.061236 \n",
+ "1 5679.643882 \n",
+ "2 5725.073334 \n",
+ "3 5876.798769 \n",
+ "4 5661.884034 \n",
".. ... \n",
- "65 3323.255445 \n",
- "66 3201.913810 \n",
- "67 3019.931424 \n",
- "68 2949.589294 \n",
- "69 2485.350227 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_2 \\\n",
- "0 0.560064 \n",
- "1 0.564508 \n",
- "2 0.568262 \n",
- "3 0.526066 \n",
- "4 0.559409 \n",
+ "65 5227.500681 \n",
+ "66 5540.710071 \n",
+ "67 5496.490785 \n",
+ "68 5456.335042 \n",
+ "69 5106.724049 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_2 \\\n",
+ "0 0.000344 \n",
+ "1 -0.026324 \n",
+ "2 -0.034534 \n",
+ "3 -0.061951 \n",
+ "4 -0.023115 \n",
".. ... \n",
- "65 0.455408 \n",
- "66 0.475293 \n",
- "67 0.505115 \n",
- "68 0.516642 \n",
- "69 0.592718 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_3 \\\n",
- "0 3485.395705 \n",
- "1 3463.798074 \n",
- "2 3578.727889 \n",
- "3 3690.510793 \n",
- "4 3489.393571 \n",
+ "65 0.063392 \n",
+ "66 0.007274 \n",
+ "67 0.015197 \n",
+ "68 0.022392 \n",
+ "69 0.085031 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_3 \\\n",
+ "0 6235.149787 \n",
+ "1 6227.670680 \n",
+ "2 6223.132210 \n",
+ "3 6321.094122 \n",
+ "4 6228.786395 \n",
".. ... \n",
- "65 4813.473905 \n",
- "66 4730.471547 \n",
- "67 4240.653693 \n",
- "68 4180.439924 \n",
- "69 3405.374928 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_3 \\\n",
- "0 0.421706 \n",
- "1 0.425289 \n",
- "2 0.406220 \n",
- "3 0.387673 \n",
- "4 0.421043 \n",
+ "65 5931.959208 \n",
+ "66 6201.689908 \n",
+ "67 5950.452784 \n",
+ "68 6101.608395 \n",
+ "69 5924.946844 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_3 \\\n",
+ "0 -0.126705 \n",
+ "1 -0.125354 \n",
+ "2 -0.124534 \n",
+ "3 -0.142236 \n",
+ "4 -0.125556 \n",
".. ... \n",
- "65 0.211202 \n",
- "66 0.224804 \n",
- "67 0.305071 \n",
- "68 0.314939 \n",
- "69 0.441951 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_4 \\\n",
- "0 3999.628256 \n",
- "1 4048.620645 \n",
- "2 4127.285053 \n",
- "3 4235.765848 \n",
- "4 4007.950448 \n",
+ "65 -0.062826 \n",
+ "66 -0.111153 \n",
+ "67 -0.066139 \n",
+ "68 -0.093222 \n",
+ "69 -0.061569 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_4 \\\n",
+ "0 6665.951971 \n",
+ "1 6600.313727 \n",
+ "2 6394.045442 \n",
+ "3 6672.065323 \n",
+ "4 6611.718967 \n",
".. ... \n",
- "65 5344.880717 \n",
- "66 5150.386860 \n",
- "67 4955.577984 \n",
- "68 5094.934816 \n",
- "69 4237.103450 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_4 \\\n",
- "0 0.336385 \n",
- "1 0.328256 \n",
- "2 0.315204 \n",
- "3 0.297205 \n",
- "4 0.335004 \n",
+ "65 6180.587308 \n",
+ "66 6467.662659 \n",
+ "67 6108.604691 \n",
+ "68 6497.883717 \n",
+ "69 6350.410974 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_4 \\\n",
+ "0 -0.204552 \n",
+ "1 -0.192691 \n",
+ "2 -0.155418 \n",
+ "3 -0.205657 \n",
+ "4 -0.194752 \n",
".. ... \n",
- "65 0.124119 \n",
- "66 0.155991 \n",
- "67 0.187915 \n",
- "68 0.165078 \n",
- "69 0.305653 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_5 \\\n",
- "0 4638.982468 \n",
- "1 4674.750775 \n",
- "2 4494.619078 \n",
- "3 4872.452681 \n",
- "4 4607.906326 \n",
+ "65 -0.107372 \n",
+ "66 -0.158807 \n",
+ "67 -0.094475 \n",
+ "68 -0.164222 \n",
+ "69 -0.137799 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_5 \\\n",
+ "0 6788.027586 \n",
+ "1 6851.937171 \n",
+ "2 6903.742081 \n",
+ "3 6942.552888 \n",
+ "4 6898.813662 \n",
".. ... \n",
- "65 5630.315250 \n",
- "66 5606.040199 \n",
- "67 5682.969251 \n",
- "68 5662.407971 \n",
- "69 5025.917365 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_5 \\\n",
- "0 0.230304 \n",
- "1 0.224369 \n",
- "2 0.254256 \n",
- "3 0.191567 \n",
- "4 0.235460 \n",
+ "65 6571.688377 \n",
+ "66 6656.869877 \n",
+ "67 6296.639581 \n",
+ "68 6312.108631 \n",
+ "69 6250.138777 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_5 \\\n",
+ "0 -0.226612 \n",
+ "1 -0.238160 \n",
+ "2 -0.247522 \n",
+ "3 -0.254535 \n",
+ "4 -0.246631 \n",
".. ... \n",
- "65 0.077344 \n",
- "66 0.081322 \n",
- "67 0.068715 \n",
- "68 0.072084 \n",
- "69 0.176388 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_6 \\\n",
- "0 5027.302770 \n",
- "1 4920.398751 \n",
- "2 5001.728634 \n",
- "3 5242.038979 \n",
- "4 5426.288241 \n",
+ "65 -0.177446 \n",
+ "66 -0.192707 \n",
+ "67 -0.128165 \n",
+ "68 -0.130937 \n",
+ "69 -0.119834 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_6 \\\n",
+ "0 7155.239308 \n",
+ "1 6859.504452 \n",
+ "2 6898.005455 \n",
+ "3 7087.736531 \n",
+ "4 6725.819832 \n",
".. ... \n",
- "65 5884.420100 \n",
- "66 5963.154321 \n",
- "67 6023.360442 \n",
- "68 5954.963272 \n",
- "69 5526.111155 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_6 \\\n",
- "0 0.165874 \n",
- "1 0.183611 \n",
- "2 0.170117 \n",
- "3 0.130245 \n",
- "4 0.099675 \n",
+ "65 6367.528123 \n",
+ "66 6731.266600 \n",
+ "67 6046.285075 \n",
+ "68 6522.814156 \n",
+ "69 6173.995273 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_6 \\\n",
+ "0 -0.292968 \n",
+ "1 -0.239528 \n",
+ "2 -0.246485 \n",
+ "3 -0.280770 \n",
+ "4 -0.215371 \n",
".. ... \n",
- "65 0.035703 \n",
- "66 0.022800 \n",
- "67 0.012934 \n",
- "68 0.024142 \n",
- "69 0.094420 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_7 \\\n",
- "0 5386.895147 \n",
- "1 5196.455731 \n",
- "2 5463.751185 \n",
- "3 5452.423985 \n",
- "4 5628.621190 \n",
+ "65 -0.140866 \n",
+ "66 -0.206037 \n",
+ "67 -0.083309 \n",
+ "68 -0.168689 \n",
+ "69 -0.106191 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_7 \\\n",
+ "0 6938.669534 \n",
+ "1 6402.080061 \n",
+ "2 6906.134630 \n",
+ "3 6931.213356 \n",
+ "4 6251.340134 \n",
".. ... \n",
- "65 6344.961992 \n",
- "66 6399.094632 \n",
- "67 6165.455206 \n",
- "68 6157.649217 \n",
- "69 6041.587390 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_7 \\\n",
- "0 0.106211 \n",
- "1 0.137808 \n",
- "2 0.093459 \n",
- "3 0.095338 \n",
- "4 0.066104 \n",
+ "65 6390.940437 \n",
+ "66 6580.335137 \n",
+ "67 5975.717171 \n",
+ "68 6243.676990 \n",
+ "69 6007.253773 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_7 \\\n",
+ "0 -0.253833 \n",
+ "1 -0.156870 \n",
+ "2 -0.247954 \n",
+ "3 -0.252486 \n",
+ "4 -0.129631 \n",
".. ... \n",
- "65 -0.039768 \n",
- "66 -0.048639 \n",
- "67 -0.010351 \n",
- "68 -0.009072 \n",
- "69 0.009947 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_8 \\\n",
- "0 5732.155126 \n",
- "1 5560.146803 \n",
- "2 5817.996707 \n",
- "3 5587.003451 \n",
- "4 5785.556238 \n",
+ "65 -0.145061 \n",
+ "66 -0.178995 \n",
+ "67 -0.070666 \n",
+ "68 -0.118676 \n",
+ "69 -0.076316 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_8 \\\n",
+ "0 6945.021356 \n",
+ "1 6190.738584 \n",
+ "2 6621.684956 \n",
+ "3 6571.907892 \n",
+ "4 5694.265877 \n",
".. ... \n",
- "65 6600.780924 \n",
- "66 6741.407424 \n",
- "67 6512.064765 \n",
- "68 6483.893137 \n",
- "69 6323.935368 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_8 \\\n",
- "0 0.048925 \n",
- "1 0.077465 \n",
- "2 0.034683 \n",
- "3 0.073009 \n",
- "4 0.040065 \n",
+ "65 6051.307223 \n",
+ "66 6519.573170 \n",
+ "67 5749.590114 \n",
+ "68 6056.418996 \n",
+ "69 5874.695827 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_8 \\\n",
+ "0 -0.254981 \n",
+ "1 -0.118680 \n",
+ "2 -0.196553 \n",
+ "3 -0.187558 \n",
+ "4 -0.028967 \n",
".. ... \n",
- "65 -0.081690 \n",
- "66 -0.104734 \n",
- "67 -0.067151 \n",
- "68 -0.062535 \n",
- "69 -0.036322 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_9 \\\n",
- "0 6017.858119 \n",
- "1 5842.122436 \n",
- "2 6094.716095 \n",
- "3 6176.740303 \n",
- "4 5987.542309 \n",
+ "65 -0.084209 \n",
+ "66 -0.168108 \n",
+ "67 -0.030151 \n",
+ "68 -0.085125 \n",
+ "69 -0.052566 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_9 \\\n",
+ "0 6428.621982 \n",
+ "1 6055.316091 \n",
+ "2 6174.979003 \n",
+ "3 6150.154721 \n",
+ "4 5427.512325 \n",
".. ... \n",
- "65 6766.067981 \n",
- "66 6921.960510 \n",
- "67 6924.629590 \n",
- "68 6980.145851 \n",
- "69 6895.975176 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_9 \\\n",
- "0 0.001522 \n",
- "1 0.030680 \n",
- "2 -0.011230 \n",
- "3 -0.024840 \n",
- "4 0.006552 \n",
+ "65 5933.424152 \n",
+ "66 6191.864619 \n",
+ "67 5741.037438 \n",
+ "68 5886.908055 \n",
+ "69 5559.283516 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_9 \\\n",
+ "0 -0.161666 \n",
+ "1 -0.094209 \n",
+ "2 -0.115832 \n",
+ "3 -0.111347 \n",
+ "4 0.019236 \n",
".. ... \n",
- "65 -0.108776 \n",
- "66 -0.134322 \n",
- "67 -0.134760 \n",
- "68 -0.143857 \n",
- "69 -0.130064 \n",
- "\n",
- " XGB_Regressor_train_MSE_after_ablation_10 \\\n",
- "0 6161.700389 \n",
- "1 6161.700389 \n",
- "2 6161.700389 \n",
- "3 6161.700389 \n",
- "4 6161.700389 \n",
+ "65 -0.063088 \n",
+ "66 -0.109393 \n",
+ "67 -0.028618 \n",
+ "68 -0.054754 \n",
+ "69 0.003946 \n",
+ "\n",
+ " Linear_train_subset_MSE_after_ablation_10 \\\n",
+ "0 5537.963738 \n",
+ "1 5537.963738 \n",
+ "2 5537.963738 \n",
+ "3 5537.963738 \n",
+ "4 5537.963738 \n",
".. ... \n",
- "65 7157.760530 \n",
- "66 7157.760530 \n",
- "67 7157.760530 \n",
- "68 7157.760530 \n",
- "69 7157.760530 \n",
- "\n",
- " XGB_Regressor_train_R_2_after_ablation_10 \\\n",
- "0 -0.022344 \n",
- "1 -0.022344 \n",
- "2 -0.022344 \n",
- "3 -0.022344 \n",
- "4 -0.022344 \n",
+ "65 5589.440875 \n",
+ "66 5589.440875 \n",
+ "67 5589.440875 \n",
+ "68 5589.440875 \n",
+ "69 5589.440875 \n",
+ "\n",
+ " Linear_train_subset_R_2_after_ablation_10 \\\n",
+ "0 -0.000722 \n",
+ "1 -0.000722 \n",
+ "2 -0.000722 \n",
+ "3 -0.000722 \n",
+ "4 -0.000722 \n",
".. ... \n",
- "65 -0.172963 \n",
- "66 -0.172963 \n",
- "67 -0.172963 \n",
- "68 -0.172963 \n",
- "69 -0.172963 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_before_ablation \\\n",
- "0 2328.348592 \n",
- "1 2328.348592 \n",
- "2 2328.348592 \n",
- "3 2328.348592 \n",
- "4 2328.348592 \n",
- ".. ... \n",
- "65 2334.402428 \n",
- "66 2334.402428 \n",
- "67 2334.402428 \n",
- "68 2334.402428 \n",
- "69 2334.402428 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_before_ablation \\\n",
- "0 0.613682 \n",
- "1 0.613682 \n",
- "2 0.613682 \n",
- "3 0.613682 \n",
- "4 0.613682 \n",
- ".. ... \n",
- "65 0.617455 \n",
- "66 0.617455 \n",
- "67 0.617455 \n",
- "68 0.617455 \n",
- "69 0.617455 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_1 \\\n",
- "0 3455.778837 \n",
- "1 3586.105224 \n",
- "2 3618.673346 \n",
- "3 3681.820673 \n",
- "4 3556.013929 \n",
- ".. ... \n",
- "65 3727.738049 \n",
- "66 3761.718243 \n",
- "67 3673.127492 \n",
- "68 3582.949000 \n",
- "69 3432.805310 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_1 \\\n",
- "0 0.426620 \n",
- "1 0.404996 \n",
- "2 0.399593 \n",
- "3 0.389115 \n",
- "4 0.409989 \n",
- ".. ... \n",
- "65 0.389124 \n",
- "66 0.383556 \n",
- "67 0.398074 \n",
- "68 0.412851 \n",
- "69 0.437456 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_2 \\\n",
- "0 4632.400024 \n",
- "1 4700.756327 \n",
- "2 4672.741484 \n",
- "3 4820.261610 \n",
- "4 4662.131533 \n",
- ".. ... \n",
- "65 4792.390428 \n",
- "66 5045.947750 \n",
- "67 4901.292728 \n",
- "68 4923.427170 \n",
- "69 4520.363739 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_2 \\\n",
- "0 0.231396 \n",
- "1 0.220054 \n",
- "2 0.224702 \n",
- "3 0.200226 \n",
- "4 0.226463 \n",
- ".. ... \n",
- "65 0.214657 \n",
- "66 0.173106 \n",
- "67 0.196811 \n",
- "68 0.193183 \n",
- "69 0.259235 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_3 \\\n",
- "0 5426.927997 \n",
- "1 5412.704307 \n",
- "2 5318.471574 \n",
- "3 5537.866064 \n",
- "4 5368.597563 \n",
- ".. ... \n",
- "65 5403.449429 \n",
- "66 5554.918333 \n",
- "67 5568.985794 \n",
- "68 5566.165474 \n",
- "69 5213.767608 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_3 \\\n",
- "0 0.099568 \n",
- "1 0.101928 \n",
- "2 0.117563 \n",
- "3 0.081162 \n",
- "4 0.109247 \n",
- ".. ... \n",
- "65 0.114521 \n",
- "66 0.089699 \n",
- "67 0.087394 \n",
- "68 0.087856 \n",
- "69 0.145604 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_4 \\\n",
- "0 5750.819366 \n",
- "1 5855.402714 \n",
- "2 5765.457023 \n",
- "3 5995.550352 \n",
- "4 5731.046785 \n",
- ".. ... \n",
- "65 5987.595488 \n",
- "66 6154.518735 \n",
- "67 5933.849628 \n",
- "68 5979.565894 \n",
- "69 5612.293318 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_4 \\\n",
- "0 0.045829 \n",
- "1 0.028476 \n",
- "2 0.043400 \n",
- "3 0.005223 \n",
- "4 0.049109 \n",
- ".. ... \n",
- "65 0.018795 \n",
- "66 -0.008559 \n",
- "67 0.027602 \n",
- "68 0.020111 \n",
- "69 0.080297 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_5 \\\n",
- "0 6024.411053 \n",
- "1 6061.293311 \n",
- "2 6003.824735 \n",
- "3 6243.577365 \n",
- "4 5894.048153 \n",
- ".. ... \n",
- "65 6134.983178 \n",
- "66 6418.420962 \n",
- "67 6067.913538 \n",
- "68 6150.733264 \n",
- "69 5905.468277 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_5 \\\n",
- "0 0.000435 \n",
- "1 -0.005685 \n",
- "2 0.003850 \n",
- "3 -0.035929 \n",
- "4 0.022064 \n",
- ".. ... \n",
- "65 -0.005358 \n",
- "66 -0.051806 \n",
- "67 0.005633 \n",
- "68 -0.007939 \n",
- "69 0.032253 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_6 \\\n",
- "0 6120.464775 \n",
- "1 6135.493568 \n",
- "2 6113.418631 \n",
- "3 6221.975848 \n",
- "4 5960.296484 \n",
- ".. ... \n",
- "65 6293.557154 \n",
- "66 6428.170085 \n",
- "67 6195.677726 \n",
- "68 6225.990012 \n",
- "69 6004.708413 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_6 \\\n",
- "0 -0.015503 \n",
- "1 -0.017996 \n",
- "2 -0.014334 \n",
- "3 -0.032345 \n",
- "4 0.011072 \n",
- ".. ... \n",
- "65 -0.031344 \n",
- "66 -0.053403 \n",
- "67 -0.015304 \n",
- "68 -0.020271 \n",
- "69 0.015991 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_7 \\\n",
- "0 6125.663086 \n",
- "1 6186.457881 \n",
- "2 6179.035357 \n",
- "3 6190.922138 \n",
- "4 6029.442460 \n",
- ".. ... \n",
- "65 6305.937749 \n",
- "66 6373.102912 \n",
- "67 6184.703036 \n",
- "68 6222.193823 \n",
- "69 6092.876970 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_7 \\\n",
- "0 -0.016365 \n",
- "1 -0.026452 \n",
- "2 -0.025221 \n",
- "3 -0.027193 \n",
- "4 -0.000400 \n",
- ".. ... \n",
- "65 -0.033373 \n",
- "66 -0.044379 \n",
- "67 -0.013506 \n",
- "68 -0.019649 \n",
- "69 0.001542 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_8 \\\n",
- "0 6092.410122 \n",
- "1 6171.165504 \n",
- "2 6148.517487 \n",
- "3 6150.480056 \n",
- "4 6041.139850 \n",
- ".. ... \n",
- "65 6243.400250 \n",
- "66 6360.759368 \n",
- "67 6165.895689 \n",
- "68 6178.858171 \n",
- "69 6096.781290 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_8 \\\n",
- "0 -0.010848 \n",
- "1 -0.023915 \n",
- "2 -0.020157 \n",
- "3 -0.020483 \n",
- "4 -0.002341 \n",
+ "65 -0.001457 \n",
+ "66 -0.001457 \n",
+ "67 -0.001457 \n",
+ "68 -0.001457 \n",
+ "69 -0.001457 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_before_ablation \\\n",
+ "0 0.018187 \n",
+ "1 0.018187 \n",
+ "2 0.018187 \n",
+ "3 0.018187 \n",
+ "4 0.018187 \n",
+ ".. ... \n",
+ "65 0.097250 \n",
+ "66 0.097250 \n",
+ "67 0.097250 \n",
+ "68 0.097250 \n",
+ "69 0.097250 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_before_ablation \\\n",
+ "0 0.999997 \n",
+ "1 0.999997 \n",
+ "2 0.999997 \n",
+ "3 0.999997 \n",
+ "4 0.999997 \n",
+ ".. ... \n",
+ "65 0.999983 \n",
+ "66 0.999983 \n",
+ "67 0.999983 \n",
+ "68 0.999983 \n",
+ "69 0.999983 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_1 \\\n",
+ "0 1625.010655 \n",
+ "1 1811.187362 \n",
+ "2 2237.078371 \n",
+ "3 2406.505913 \n",
+ "4 1760.246456 \n",
+ ".. ... \n",
+ "65 1409.122866 \n",
+ "66 1548.709747 \n",
+ "67 1377.246667 \n",
+ "68 1401.369064 \n",
+ "69 1615.258137 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_1 \\\n",
+ "0 0.706357 \n",
+ "1 0.672714 \n",
+ "2 0.595755 \n",
+ "3 0.565139 \n",
+ "4 0.681920 \n",
+ ".. ... \n",
+ "65 0.747528 \n",
+ "66 0.722519 \n",
+ "67 0.753240 \n",
+ "68 0.748918 \n",
+ "69 0.710595 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_2 \\\n",
+ "0 3727.227862 \n",
+ "1 3768.911516 \n",
+ "2 3839.017846 \n",
+ "3 3694.557248 \n",
+ "4 3902.301179 \n",
+ ".. ... \n",
+ "65 3062.737215 \n",
+ "66 3239.161380 \n",
+ "67 3380.234480 \n",
+ "68 3294.968987 \n",
+ "69 2988.046101 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_2 \\\n",
+ "0 0.326482 \n",
+ "1 0.318949 \n",
+ "2 0.306281 \n",
+ "3 0.332385 \n",
+ "4 0.294845 \n",
+ ".. ... \n",
+ "65 0.451251 \n",
+ "66 0.419641 \n",
+ "67 0.394365 \n",
+ "68 0.409642 \n",
+ "69 0.464634 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_3 \\\n",
+ "0 4758.802828 \n",
+ "1 4799.059708 \n",
+ "2 4761.200794 \n",
+ "3 4731.899147 \n",
+ "4 4786.063094 \n",
+ ".. ... \n",
+ "65 4143.180980 \n",
+ "66 4348.167990 \n",
+ "67 4584.976546 \n",
+ "68 4350.842152 \n",
+ "69 3961.078843 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_3 \\\n",
+ "0 0.140074 \n",
+ "1 0.132799 \n",
+ "2 0.139640 \n",
+ "3 0.144935 \n",
+ "4 0.135148 \n",
+ ".. ... \n",
+ "65 0.257669 \n",
+ "66 0.220941 \n",
+ "67 0.178512 \n",
+ "68 0.220462 \n",
+ "69 0.290296 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_4 \\\n",
+ "0 5438.045521 \n",
+ "1 5389.715225 \n",
+ "2 5044.732487 \n",
+ "3 5392.714460 \n",
+ "4 5248.502766 \n",
+ ".. ... \n",
+ "65 4973.750342 \n",
+ "66 5168.590233 \n",
+ "67 5219.394868 \n",
+ "68 5097.939455 \n",
+ "69 4916.360392 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_4 \\\n",
+ "0 0.017333 \n",
+ "1 0.026066 \n",
+ "2 0.088406 \n",
+ "3 0.025524 \n",
+ "4 0.051584 \n",
+ ".. ... \n",
+ "65 0.108856 \n",
+ "66 0.073947 \n",
+ "67 0.064844 \n",
+ "68 0.086605 \n",
+ "69 0.119139 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_5 \\\n",
+ "0 6086.223432 \n",
+ "1 5710.096369 \n",
+ "2 5393.980964 \n",
+ "3 5774.949568 \n",
+ "4 5562.326281 \n",
+ ".. ... \n",
+ "65 5579.904958 \n",
+ "66 5650.278499 \n",
+ "67 5552.852007 \n",
+ "68 5404.702722 \n",
+ "69 5129.675910 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_5 \\\n",
+ "0 -0.099794 \n",
+ "1 -0.031827 \n",
+ "2 0.025296 \n",
+ "3 -0.043546 \n",
+ "4 -0.005125 \n",
+ ".. ... \n",
+ "65 0.000252 \n",
+ "66 -0.012357 \n",
+ "67 0.005099 \n",
+ "68 0.031643 \n",
+ "69 0.080919 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_6 \\\n",
+ "0 6003.810755 \n",
+ "1 5721.904769 \n",
+ "2 5405.528810 \n",
+ "3 5789.624542 \n",
+ "4 5666.256209 \n",
+ ".. ... \n",
+ "65 5919.620840 \n",
+ "66 6010.622799 \n",
+ "67 5657.061402 \n",
+ "68 5415.757183 \n",
+ "69 5402.084447 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_6 \\\n",
+ "0 -0.084902 \n",
+ "1 -0.033961 \n",
+ "2 0.023209 \n",
+ "3 -0.046198 \n",
+ "4 -0.023905 \n",
+ ".. ... \n",
+ "65 -0.060615 \n",
+ "66 -0.076920 \n",
+ "67 -0.013572 \n",
+ "68 0.029662 \n",
+ "69 0.032112 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_7 \\\n",
+ "0 5914.676886 \n",
+ "1 5982.301528 \n",
+ "2 5693.370483 \n",
+ "3 5932.103010 \n",
+ "4 5825.740431 \n",
+ ".. ... \n",
+ "65 5991.195842 \n",
+ "66 6015.874192 \n",
+ "67 5778.266563 \n",
+ "68 5649.120636 \n",
+ "69 5347.120892 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_7 \\\n",
+ "0 -0.068795 \n",
+ "1 -0.081015 \n",
+ "2 -0.028805 \n",
+ "3 -0.071944 \n",
+ "4 -0.052724 \n",
+ ".. ... \n",
+ "65 -0.073439 \n",
+ "66 -0.077861 \n",
+ "67 -0.035289 \n",
+ "68 -0.012150 \n",
+ "69 0.041960 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_8 \\\n",
+ "0 5957.839900 \n",
+ "1 6049.655530 \n",
+ "2 5814.666743 \n",
+ "3 6000.631989 \n",
+ "4 5924.347912 \n",
+ ".. ... \n",
+ "65 5815.187326 \n",
+ "66 5992.264780 \n",
+ "67 5632.206444 \n",
+ "68 5755.516127 \n",
+ "69 5635.222335 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_8 \\\n",
+ "0 -0.076595 \n",
+ "1 -0.093186 \n",
+ "2 -0.050723 \n",
+ "3 -0.084328 \n",
+ "4 -0.070543 \n",
+ ".. ... \n",
+ "65 -0.041904 \n",
+ "66 -0.073631 \n",
+ "67 -0.009119 \n",
+ "68 -0.031212 \n",
+ "69 -0.009659 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_9 \\\n",
+ "0 6074.783783 \n",
+ "1 6140.066210 \n",
+ "2 5905.232497 \n",
+ "3 6064.504349 \n",
+ "4 6003.463504 \n",
+ ".. ... \n",
+ "65 5869.966012 \n",
+ "66 5818.049908 \n",
+ "67 5673.012560 \n",
+ "68 5785.642537 \n",
+ "69 5650.083279 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_9 \\\n",
+ "0 -0.097727 \n",
+ "1 -0.109524 \n",
+ "2 -0.067089 \n",
+ "3 -0.095869 \n",
+ "4 -0.084839 \n",
+ ".. ... \n",
+ "65 -0.051718 \n",
+ "66 -0.042417 \n",
+ "67 -0.016430 \n",
+ "68 -0.036610 \n",
+ "69 -0.012322 \n",
+ "\n",
+ " XGB_Regressor_train_subset_MSE_after_ablation_10 \\\n",
+ "0 6105.231363 \n",
+ "1 6105.231363 \n",
+ "2 6105.231363 \n",
+ "3 6105.231363 \n",
+ "4 6105.231363 \n",
+ ".. ... \n",
+ "65 5611.310265 \n",
+ "66 5611.310265 \n",
+ "67 5611.310265 \n",
+ "68 5611.310265 \n",
+ "69 5611.310265 \n",
+ "\n",
+ " XGB_Regressor_train_subset_R_2_after_ablation_10 \\\n",
+ "0 -0.103229 \n",
+ "1 -0.103229 \n",
+ "2 -0.103229 \n",
+ "3 -0.103229 \n",
+ "4 -0.103229 \n",
+ ".. ... \n",
+ "65 -0.005375 \n",
+ "66 -0.005375 \n",
+ "67 -0.005375 \n",
+ "68 -0.005375 \n",
+ "69 -0.005375 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_before_ablation \\\n",
+ "0 2144.267875 \n",
+ "1 2144.267875 \n",
+ "2 2144.267875 \n",
+ "3 2144.267875 \n",
+ "4 2144.267875 \n",
+ ".. ... \n",
+ "65 2193.167972 \n",
+ "66 2193.167972 \n",
+ "67 2193.167972 \n",
+ "68 2193.167972 \n",
+ "69 2193.167972 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_before_ablation \\\n",
+ "0 0.612526 \n",
+ "1 0.612526 \n",
+ "2 0.612526 \n",
+ "3 0.612526 \n",
+ "4 0.612526 \n",
+ ".. ... \n",
+ "65 0.607051 \n",
+ "66 0.607051 \n",
+ "67 0.607051 \n",
+ "68 0.607051 \n",
+ "69 0.607051 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_1 \\\n",
+ "0 3060.549288 \n",
+ "1 3176.445261 \n",
+ "2 3504.405453 \n",
+ "3 3646.878671 \n",
+ "4 3208.000445 \n",
+ ".. ... \n",
+ "65 3333.951885 \n",
+ "66 3464.273155 \n",
+ "67 3313.295136 \n",
+ "68 3289.911059 \n",
+ "69 3380.287738 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_1 \\\n",
+ "0 0.446952 \n",
+ "1 0.426009 \n",
+ "2 0.366746 \n",
+ "3 0.341001 \n",
+ "4 0.420307 \n",
+ ".. ... \n",
+ "65 0.402658 \n",
+ "66 0.379308 \n",
+ "67 0.406359 \n",
+ "68 0.410549 \n",
+ "69 0.394356 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_2 \\\n",
+ "0 4420.021303 \n",
+ "1 4460.833780 \n",
+ "2 4469.713519 \n",
+ "3 4609.859327 \n",
+ "4 4583.943975 \n",
+ ".. ... \n",
+ "65 4568.961153 \n",
+ "66 4770.751640 \n",
+ "67 4771.879930 \n",
+ "68 4688.223178 \n",
+ "69 4332.850804 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_2 \\\n",
+ "0 0.201292 \n",
+ "1 0.193917 \n",
+ "2 0.192313 \n",
+ "3 0.166988 \n",
+ "4 0.171671 \n",
+ ".. ... \n",
+ "65 0.181382 \n",
+ "66 0.145227 \n",
+ "67 0.145025 \n",
+ "68 0.160014 \n",
+ "69 0.223686 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_3 \\\n",
+ "0 5162.192629 \n",
+ "1 5097.059761 \n",
+ "2 5063.344675 \n",
+ "3 5163.674782 \n",
+ "4 5270.742639 \n",
+ ".. ... \n",
+ "65 5193.217918 \n",
+ "66 5395.283077 \n",
+ "67 5267.557812 \n",
+ "68 5262.297817 \n",
+ "69 5002.140836 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_3 \\\n",
+ "0 0.067180 \n",
+ "1 0.078950 \n",
+ "2 0.085042 \n",
+ "3 0.066912 \n",
+ "4 0.047565 \n",
+ ".. ... \n",
+ "65 0.069534 \n",
+ "66 0.033330 \n",
+ "67 0.056215 \n",
+ "68 0.057157 \n",
+ "69 0.103769 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_4 \\\n",
+ "0 5474.959682 \n",
+ "1 5485.856853 \n",
+ "2 5430.198772 \n",
+ "3 5654.780863 \n",
+ "4 5593.220279 \n",
+ ".. ... \n",
+ "65 5516.575047 \n",
+ "66 5795.554139 \n",
+ "67 5407.976223 \n",
+ "68 5572.520393 \n",
+ "69 5500.719456 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_4 \\\n",
+ "0 0.010663 \n",
+ "1 0.008693 \n",
+ "2 0.018751 \n",
+ "3 -0.021832 \n",
+ "4 -0.010707 \n",
+ ".. ... \n",
+ "65 0.011599 \n",
+ "66 -0.038386 \n",
+ "67 0.031056 \n",
+ "68 0.001575 \n",
+ "69 0.014439 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_5 \\\n",
+ "0 5641.270595 \n",
+ "1 5608.567209 \n",
+ "2 5629.508352 \n",
+ "3 5761.998372 \n",
+ "4 5575.129386 \n",
+ ".. ... \n",
+ "65 5795.097195 \n",
+ "66 5967.401983 \n",
+ "67 5588.330353 \n",
+ "68 5626.114993 \n",
+ "69 5462.943959 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_5 \\\n",
+ "0 -0.019390 \n",
+ "1 -0.013481 \n",
+ "2 -0.017265 \n",
+ "3 -0.041206 \n",
+ "4 -0.007438 \n",
+ ".. ... \n",
+ "65 -0.038304 \n",
+ "66 -0.069176 \n",
+ "67 -0.001258 \n",
+ "68 -0.008028 \n",
+ "69 0.021208 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_6 \\\n",
+ "0 5661.113577 \n",
+ "1 5606.850647 \n",
+ "2 5623.779888 \n",
+ "3 5689.750699 \n",
+ "4 5534.621890 \n",
+ ".. ... \n",
+ "65 5708.668205 \n",
+ "66 5938.818272 \n",
+ "67 5597.096985 \n",
+ "68 5720.182130 \n",
+ "69 5509.389569 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_6 \\\n",
+ "0 -0.022976 \n",
+ "1 -0.013170 \n",
+ "2 -0.016230 \n",
+ "3 -0.028151 \n",
+ "4 -0.000119 \n",
+ ".. ... \n",
+ "65 -0.022819 \n",
+ "66 -0.064055 \n",
+ "67 -0.002829 \n",
+ "68 -0.024882 \n",
+ "69 0.012886 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_7 \\\n",
+ "0 5588.716961 \n",
+ "1 5631.777151 \n",
+ "2 5604.950211 \n",
+ "3 5675.115137 \n",
+ "4 5561.347439 \n",
+ ".. ... \n",
+ "65 5806.308659 \n",
+ "66 5911.916236 \n",
+ "67 5599.602808 \n",
+ "68 5708.412501 \n",
+ "69 5502.215052 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_7 \\\n",
+ "0 -0.009894 \n",
+ "1 -0.017675 \n",
+ "2 -0.012827 \n",
+ "3 -0.025506 \n",
+ "4 -0.004948 \n",
+ ".. ... \n",
+ "65 -0.040313 \n",
+ "66 -0.059235 \n",
+ "67 -0.003278 \n",
+ "68 -0.022773 \n",
+ "69 0.014171 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_8 \\\n",
+ "0 5570.355417 \n",
+ "1 5627.949257 \n",
+ "2 5580.016962 \n",
+ "3 5635.679423 \n",
+ "4 5576.001782 \n",
+ ".. ... \n",
+ "65 5724.849106 \n",
+ "66 5826.379101 \n",
+ "67 5660.876322 \n",
+ "68 5673.183423 \n",
+ "69 5581.847580 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_8 \\\n",
+ "0 -0.006576 \n",
+ "1 -0.016983 \n",
+ "2 -0.008322 \n",
+ "3 -0.018380 \n",
+ "4 -0.007596 \n",
+ ".. ... \n",
+ "65 -0.025718 \n",
+ "66 -0.043909 \n",
+ "67 -0.014256 \n",
+ "68 -0.016461 \n",
+ "69 -0.000096 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_9 \\\n",
+ "0 5583.728055 \n",
+ "1 5616.876738 \n",
+ "2 5602.884260 \n",
+ "3 5607.887542 \n",
+ "4 5575.467267 \n",
+ ".. ... \n",
+ "65 5763.980812 \n",
+ "66 5723.786894 \n",
+ "67 5635.083783 \n",
+ "68 5664.500329 \n",
+ "69 5593.342518 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_9 \\\n",
+ "0 -0.008992 \n",
+ "1 -0.014982 \n",
+ "2 -0.012454 \n",
+ "3 -0.013358 \n",
+ "4 -0.007499 \n",
+ ".. ... \n",
+ "65 -0.032729 \n",
+ "66 -0.025528 \n",
+ "67 -0.009635 \n",
+ "68 -0.014905 \n",
+ "69 -0.002156 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_MSE_after_ablation_10 \\\n",
+ "0 5566.322332 \n",
+ "1 5566.322332 \n",
+ "2 5566.322332 \n",
+ "3 5566.322332 \n",
+ "4 5566.322332 \n",
+ ".. ... \n",
+ "65 5624.090066 \n",
+ "66 5624.090066 \n",
+ "67 5624.090066 \n",
+ "68 5624.090066 \n",
+ "69 5624.090066 \n",
+ "\n",
+ " RF_Plus_Regressor_train_subset_R_2_after_ablation_10 \\\n",
+ "0 -0.005847 \n",
+ "1 -0.005847 \n",
+ "2 -0.005847 \n",
+ "3 -0.005847 \n",
+ "4 -0.005847 \n",
+ ".. ... \n",
+ "65 -0.007665 \n",
+ "66 -0.007665 \n",
+ "67 -0.007665 \n",
+ "68 -0.007665 \n",
+ "69 -0.007665 \n",
+ "\n",
+ " train_subset_ablation_time RF_Regressor_test_subset_MSE_before_ablation \\\n",
+ "0 8.492494 2679.064560 \n",
+ "1 8.477902 2679.064560 \n",
+ "2 8.412474 2679.064560 \n",
+ "3 8.385556 2679.064560 \n",
+ "4 8.385494 2679.064560 \n",
+ ".. ... ... \n",
+ "65 9.516454 3509.831927 \n",
+ "66 9.597552 3509.831927 \n",
+ "67 9.634410 3509.831927 \n",
+ "68 9.592882 3509.831927 \n",
+ "69 9.586439 3509.831927 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_before_ablation \\\n",
+ "0 0.542605 \n",
+ "1 0.542605 \n",
+ "2 0.542605 \n",
+ "3 0.542605 \n",
+ "4 0.542605 \n",
".. ... \n",
- "65 -0.023125 \n",
- "66 -0.042357 \n",
- "67 -0.010424 \n",
- "68 -0.012548 \n",
- "69 0.000902 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_9 \\\n",
- "0 6050.975584 \n",
- "1 6102.377688 \n",
- "2 6098.941000 \n",
- "3 6103.170216 \n",
- "4 6036.782692 \n",
+ "65 0.426241 \n",
+ "66 0.426241 \n",
+ "67 0.426241 \n",
+ "68 0.426241 \n",
+ "69 0.426241 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_1 \\\n",
+ "0 3558.027039 \n",
+ "1 3580.553278 \n",
+ "2 3480.440454 \n",
+ "3 3476.115995 \n",
+ "4 3467.889825 \n",
+ ".. ... \n",
+ "65 4213.771834 \n",
+ "66 4244.202125 \n",
+ "67 4405.069590 \n",
+ "68 4364.788724 \n",
+ "69 4198.773435 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_1 \\\n",
+ "0 0.392540 \n",
+ "1 0.388694 \n",
+ "2 0.405786 \n",
+ "3 0.406525 \n",
+ "4 0.407929 \n",
+ ".. ... \n",
+ "65 0.311166 \n",
+ "66 0.306192 \n",
+ "67 0.279894 \n",
+ "68 0.286479 \n",
+ "69 0.313618 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_2 \\\n",
+ "0 4541.111469 \n",
+ "1 4515.904516 \n",
+ "2 4428.797618 \n",
+ "3 4606.954160 \n",
+ "4 4522.247977 \n",
+ ".. ... \n",
+ "65 4825.940412 \n",
+ "66 5180.216168 \n",
+ "67 5324.958907 \n",
+ "68 5096.309073 \n",
+ "69 5217.671821 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_2 \\\n",
+ "0 0.224698 \n",
+ "1 0.229002 \n",
+ "2 0.243874 \n",
+ "3 0.213457 \n",
+ "4 0.227919 \n",
+ ".. ... \n",
+ "65 0.211094 \n",
+ "66 0.153179 \n",
+ "67 0.129518 \n",
+ "68 0.166896 \n",
+ "69 0.147057 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_3 \\\n",
+ "0 5108.780808 \n",
+ "1 5136.563348 \n",
+ "2 5106.507299 \n",
+ "3 5308.753320 \n",
+ "4 5062.186749 \n",
+ ".. ... \n",
+ "65 5681.011294 \n",
+ "66 5853.344850 \n",
+ "67 5969.752485 \n",
+ "68 5689.664778 \n",
+ "69 5693.938662 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_3 \\\n",
+ "0 0.127781 \n",
+ "1 0.123037 \n",
+ "2 0.128169 \n",
+ "3 0.093639 \n",
+ "4 0.135736 \n",
+ ".. ... \n",
+ "65 0.071313 \n",
+ "66 0.043142 \n",
+ "67 0.024112 \n",
+ "68 0.069899 \n",
+ "69 0.069200 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_4 \\\n",
+ "0 5549.938512 \n",
+ "1 5524.671544 \n",
+ "2 5529.201248 \n",
+ "3 5626.772122 \n",
+ "4 5125.361953 \n",
+ ".. ... \n",
+ "65 6040.236320 \n",
+ "66 6059.064892 \n",
+ "67 6107.021507 \n",
+ "68 6158.371502 \n",
+ "69 6112.809648 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_4 \\\n",
+ "0 0.052462 \n",
+ "1 0.056776 \n",
+ "2 0.056002 \n",
+ "3 0.039344 \n",
+ "4 0.124950 \n",
+ ".. ... \n",
+ "65 0.012590 \n",
+ "66 0.009512 \n",
+ "67 0.001673 \n",
+ "68 -0.006722 \n",
+ "69 0.000727 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_5 \\\n",
+ "0 5575.079768 \n",
+ "1 5632.072864 \n",
+ "2 5617.274206 \n",
+ "3 5688.953069 \n",
+ "4 5403.866778 \n",
+ ".. ... \n",
+ "65 6010.251621 \n",
+ "66 6033.072523 \n",
+ "67 6094.252440 \n",
+ "68 6203.838469 \n",
+ "69 6071.081040 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_5 \\\n",
+ "0 0.048170 \n",
+ "1 0.038439 \n",
+ "2 0.040966 \n",
+ "3 0.028728 \n",
+ "4 0.077401 \n",
+ ".. ... \n",
+ "65 0.017492 \n",
+ "66 0.013761 \n",
+ "67 0.003760 \n",
+ "68 -0.014154 \n",
+ "69 0.007548 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_6 \\\n",
+ "0 5670.569231 \n",
+ "1 5732.292023 \n",
+ "2 5691.562223 \n",
+ "3 5665.064149 \n",
+ "4 5605.699200 \n",
+ ".. ... \n",
+ "65 6040.809248 \n",
+ "66 6076.452794 \n",
+ "67 6125.304668 \n",
+ "68 6310.867104 \n",
+ "69 6126.095327 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_6 \\\n",
+ "0 0.031867 \n",
+ "1 0.021329 \n",
+ "2 0.028283 \n",
+ "3 0.032807 \n",
+ "4 0.042942 \n",
+ ".. ... \n",
+ "65 0.012497 \n",
+ "66 0.006670 \n",
+ "67 -0.001316 \n",
+ "68 -0.031650 \n",
+ "69 -0.001445 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_7 \\\n",
+ "0 5714.830950 \n",
+ "1 5748.309155 \n",
+ "2 5752.950476 \n",
+ "3 5725.081827 \n",
+ "4 5672.867376 \n",
+ ".. ... \n",
+ "65 6072.462142 \n",
+ "66 6163.188391 \n",
+ "67 6099.205558 \n",
+ "68 6234.113582 \n",
+ "69 6212.118697 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_7 \\\n",
+ "0 0.024310 \n",
+ "1 0.018594 \n",
+ "2 0.017802 \n",
+ "3 0.022560 \n",
+ "4 0.031474 \n",
+ ".. ... \n",
+ "65 0.007322 \n",
+ "66 -0.007509 \n",
+ "67 0.002950 \n",
+ "68 -0.019103 \n",
+ "69 -0.015508 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_8 \\\n",
+ "0 5776.424753 \n",
+ "1 5834.804713 \n",
+ "2 5833.262844 \n",
+ "3 5843.531281 \n",
+ "4 5812.376227 \n",
+ ".. ... \n",
+ "65 6219.755407 \n",
+ "66 6167.744088 \n",
+ "67 6128.170963 \n",
+ "68 6146.976283 \n",
+ "69 6156.865589 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_8 \\\n",
+ "0 0.013794 \n",
+ "1 0.003827 \n",
+ "2 0.004090 \n",
+ "3 0.002337 \n",
+ "4 0.007656 \n",
+ ".. ... \n",
+ "65 -0.016756 \n",
+ "66 -0.008254 \n",
+ "67 -0.001785 \n",
+ "68 -0.004859 \n",
+ "69 -0.006475 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_9 \\\n",
+ "0 5872.761365 \n",
+ "1 5893.413600 \n",
+ "2 5842.980649 \n",
+ "3 5897.607209 \n",
+ "4 5867.281714 \n",
+ ".. ... \n",
+ "65 6225.621623 \n",
+ "66 6163.381267 \n",
+ "67 6156.521984 \n",
+ "68 6087.385960 \n",
+ "69 6109.418689 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_9 \\\n",
+ "0 -0.002653 \n",
+ "1 -0.006179 \n",
+ "2 0.002431 \n",
+ "3 -0.006895 \n",
+ "4 -0.001718 \n",
+ ".. ... \n",
+ "65 -0.017715 \n",
+ "66 -0.007541 \n",
+ "67 -0.006419 \n",
+ "68 0.004883 \n",
+ "69 0.001281 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_10 \\\n",
+ "0 5889.339711 \n",
+ "1 5889.339711 \n",
+ "2 5889.339711 \n",
+ "3 5889.339711 \n",
+ "4 5889.339711 \n",
+ ".. ... \n",
+ "65 6148.928735 \n",
+ "66 6148.928735 \n",
+ "67 6148.928735 \n",
+ "68 6148.928735 \n",
+ "69 6148.928735 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_10 \\\n",
+ "0 -0.005484 \n",
+ "1 -0.005484 \n",
+ "2 -0.005484 \n",
+ "3 -0.005484 \n",
+ "4 -0.005484 \n",
+ ".. ... \n",
+ "65 -0.005178 \n",
+ "66 -0.005178 \n",
+ "67 -0.005178 \n",
+ "68 -0.005178 \n",
+ "69 -0.005178 \n",
+ "\n",
+ " Linear_test_subset_MSE_before_ablation \\\n",
+ "0 2565.576138 \n",
+ "1 2565.576138 \n",
+ "2 2565.576138 \n",
+ "3 2565.576138 \n",
+ "4 2565.576138 \n",
+ ".. ... \n",
+ "65 3546.190517 \n",
+ "66 3546.190517 \n",
+ "67 3546.190517 \n",
+ "68 3546.190517 \n",
+ "69 3546.190517 \n",
+ "\n",
+ " Linear_test_subset_R_2_before_ablation \\\n",
+ "0 0.561981 \n",
+ "1 0.561981 \n",
+ "2 0.561981 \n",
+ "3 0.561981 \n",
+ "4 0.561981 \n",
+ ".. ... \n",
+ "65 0.420297 \n",
+ "66 0.420297 \n",
+ "67 0.420297 \n",
+ "68 0.420297 \n",
+ "69 0.420297 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_1 \\\n",
+ "0 4121.029876 \n",
+ "1 4124.763026 \n",
+ "2 3756.267014 \n",
+ "3 3915.996792 \n",
+ "4 4094.432088 \n",
+ ".. ... \n",
+ "65 4317.195582 \n",
+ "66 4298.706761 \n",
+ "67 4666.607280 \n",
+ "68 4665.190648 \n",
+ "69 4451.421766 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_1 \\\n",
+ "0 0.296419 \n",
+ "1 0.295781 \n",
+ "2 0.358695 \n",
+ "3 0.331424 \n",
+ "4 0.300960 \n",
+ ".. ... \n",
+ "65 0.294259 \n",
+ "66 0.297282 \n",
+ "67 0.237140 \n",
+ "68 0.237372 \n",
+ "69 0.272317 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_2 \\\n",
+ "0 5581.975377 \n",
+ "1 5536.778873 \n",
+ "2 5052.597617 \n",
+ "3 5378.766021 \n",
+ "4 5533.852742 \n",
+ ".. ... \n",
+ "65 5220.529078 \n",
+ "66 5543.796750 \n",
+ "67 5609.077406 \n",
+ "68 5658.394843 \n",
+ "69 5624.555118 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_2 \\\n",
+ "0 0.046992 \n",
+ "1 0.054709 \n",
+ "2 0.137373 \n",
+ "3 0.081686 \n",
+ "4 0.055208 \n",
+ ".. ... \n",
+ "65 0.146589 \n",
+ "66 0.093744 \n",
+ "67 0.083073 \n",
+ "68 0.075011 \n",
+ "69 0.080542 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_3 \\\n",
+ "0 6449.756912 \n",
+ "1 6523.833742 \n",
+ "2 5888.265223 \n",
+ "3 6371.788379 \n",
+ "4 6551.561645 \n",
+ ".. ... \n",
+ "65 6400.227369 \n",
+ "66 6597.919515 \n",
+ "67 6687.347282 \n",
+ "68 6659.387508 \n",
+ "69 6568.669569 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_3 \\\n",
+ "0 -0.101164 \n",
+ "1 -0.113811 \n",
+ "2 -0.005300 \n",
+ "3 -0.087852 \n",
+ "4 -0.118545 \n",
+ ".. ... \n",
+ "65 -0.046258 \n",
+ "66 -0.078575 \n",
+ "67 -0.093194 \n",
+ "68 -0.088624 \n",
+ "69 -0.073794 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_4 \\\n",
+ "0 6842.982437 \n",
+ "1 7003.490348 \n",
+ "2 6474.285892 \n",
+ "3 6745.355899 \n",
+ "4 6861.311919 \n",
+ ".. ... \n",
+ "65 6949.837827 \n",
+ "66 7200.544735 \n",
+ "67 7219.572194 \n",
+ "68 7340.405511 \n",
+ "69 7205.254833 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_4 \\\n",
+ "0 -0.168299 \n",
+ "1 -0.195702 \n",
+ "2 -0.105351 \n",
+ "3 -0.151631 \n",
+ "4 -0.171428 \n",
+ ".. ... \n",
+ "65 -0.136104 \n",
+ "66 -0.177088 \n",
+ "67 -0.180198 \n",
+ "68 -0.199951 \n",
+ "69 -0.177858 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_5 \\\n",
+ "0 7065.868591 \n",
+ "1 7133.726667 \n",
+ "2 6949.460302 \n",
+ "3 7002.600058 \n",
+ "4 7429.580019 \n",
+ ".. ... \n",
+ "65 7213.551738 \n",
+ "66 7180.863666 \n",
+ "67 7191.487748 \n",
+ "68 7230.734184 \n",
+ "69 7368.282965 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_5 \\\n",
+ "0 -0.206352 \n",
+ "1 -0.217937 \n",
+ "2 -0.186478 \n",
+ "3 -0.195550 \n",
+ "4 -0.268448 \n",
+ ".. ... \n",
+ "65 -0.179214 \n",
+ "66 -0.173870 \n",
+ "67 -0.175607 \n",
+ "68 -0.182023 \n",
+ "69 -0.204508 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_6 \\\n",
+ "0 7600.334465 \n",
+ "1 7427.707370 \n",
+ "2 7443.807580 \n",
+ "3 7370.100410 \n",
+ "4 6950.073027 \n",
+ ".. ... \n",
+ "65 7144.965343 \n",
+ "66 7178.534520 \n",
+ "67 7079.444666 \n",
+ "68 7129.372180 \n",
+ "69 7365.857893 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_6 \\\n",
+ "0 -0.297601 \n",
+ "1 -0.268129 \n",
+ "2 -0.270877 \n",
+ "3 -0.258293 \n",
+ "4 -0.186582 \n",
+ ".. ... \n",
+ "65 -0.168002 \n",
+ "66 -0.173490 \n",
+ "67 -0.157291 \n",
+ "68 -0.165453 \n",
+ "69 -0.204112 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_7 \\\n",
+ "0 7801.583405 \n",
+ "1 7647.662285 \n",
+ "2 7688.902103 \n",
+ "3 7607.256541 \n",
+ "4 6638.554918 \n",
+ ".. ... \n",
+ "65 7042.816321 \n",
+ "66 7282.307820 \n",
+ "67 6516.825963 \n",
+ "68 6842.169559 \n",
+ "69 7235.050354 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_7 \\\n",
+ "0 -0.331960 \n",
+ "1 -0.305681 \n",
+ "2 -0.312722 \n",
+ "3 -0.298783 \n",
+ "4 -0.133397 \n",
+ ".. ... \n",
+ "65 -0.151304 \n",
+ "66 -0.190454 \n",
+ "67 -0.065319 \n",
+ "68 -0.118503 \n",
+ "69 -0.182728 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_8 \\\n",
+ "0 7891.538915 \n",
+ "1 6644.842594 \n",
+ "2 7609.910506 \n",
+ "3 7853.630412 \n",
+ "4 6173.376633 \n",
+ ".. ... \n",
+ "65 6800.197216 \n",
+ "66 7045.106442 \n",
+ "67 6264.367986 \n",
+ "68 6660.330947 \n",
+ "69 6319.121485 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_8 \\\n",
+ "0 -0.347318 \n",
+ "1 -0.134470 \n",
+ "2 -0.299236 \n",
+ "3 -0.340846 \n",
+ "4 -0.053977 \n",
+ ".. ... \n",
+ "65 -0.111642 \n",
+ "66 -0.151678 \n",
+ "67 -0.024049 \n",
+ "68 -0.088778 \n",
+ "69 -0.033000 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_9 \\\n",
+ "0 6808.265390 \n",
+ "1 6017.978299 \n",
+ "2 6630.493971 \n",
+ "3 6995.518004 \n",
+ "4 5914.424323 \n",
+ ".. ... \n",
+ "65 6382.959926 \n",
+ "66 6518.753085 \n",
+ "67 6157.597738 \n",
+ "68 6404.891031 \n",
+ "69 6286.420406 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_9 \\\n",
+ "0 -0.162372 \n",
+ "1 -0.027446 \n",
+ "2 -0.132021 \n",
+ "3 -0.194341 \n",
+ "4 -0.009767 \n",
+ ".. ... \n",
+ "65 -0.043436 \n",
+ "66 -0.065634 \n",
+ "67 -0.006595 \n",
+ "68 -0.047021 \n",
+ "69 -0.027654 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_10 \\\n",
+ "0 5858.937117 \n",
+ "1 5858.937117 \n",
+ "2 5858.937117 \n",
+ "3 5858.937117 \n",
+ "4 5858.937117 \n",
+ ".. ... \n",
+ "65 6120.597362 \n",
+ "66 6120.597362 \n",
+ "67 6120.597362 \n",
+ "68 6120.597362 \n",
+ "69 6120.597362 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_10 \\\n",
+ "0 -0.000293 \n",
+ "1 -0.000293 \n",
+ "2 -0.000293 \n",
+ "3 -0.000293 \n",
+ "4 -0.000293 \n",
+ ".. ... \n",
+ "65 -0.000547 \n",
+ "66 -0.000547 \n",
+ "67 -0.000547 \n",
+ "68 -0.000547 \n",
+ "69 -0.000547 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_before_ablation \\\n",
+ "0 3557.841426 \n",
+ "1 3557.841426 \n",
+ "2 3557.841426 \n",
+ "3 3557.841426 \n",
+ "4 3557.841426 \n",
+ ".. ... \n",
+ "65 4204.805826 \n",
+ "66 4204.805826 \n",
+ "67 4204.805826 \n",
+ "68 4204.805826 \n",
+ "69 4204.805826 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_before_ablation \\\n",
+ "0 0.392572 \n",
+ "1 0.392572 \n",
+ "2 0.392572 \n",
+ "3 0.392572 \n",
+ "4 0.392572 \n",
+ ".. ... \n",
+ "65 0.312632 \n",
+ "66 0.312632 \n",
+ "67 0.312632 \n",
+ "68 0.312632 \n",
+ "69 0.312632 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_1 \\\n",
+ "0 3667.804311 \n",
+ "1 3683.765603 \n",
+ "2 3778.080730 \n",
+ "3 3801.245390 \n",
+ "4 3734.806153 \n",
+ ".. ... \n",
+ "65 4532.535944 \n",
+ "66 4539.464977 \n",
+ "67 4889.411544 \n",
+ "68 4832.984280 \n",
+ "69 4729.606612 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_1 \\\n",
+ "0 0.373798 \n",
+ "1 0.371073 \n",
+ "2 0.354970 \n",
+ "3 0.351015 \n",
+ "4 0.362359 \n",
+ ".. ... \n",
+ "65 0.259057 \n",
+ "66 0.257924 \n",
+ "67 0.200718 \n",
+ "68 0.209942 \n",
+ "69 0.226842 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_2 \\\n",
+ "0 5488.665183 \n",
+ "1 5290.726366 \n",
+ "2 4892.289472 \n",
+ "3 5113.264624 \n",
+ "4 5403.526760 \n",
+ ".. ... \n",
+ "65 4782.177425 \n",
+ "66 5165.616795 \n",
+ "67 5347.951315 \n",
+ "68 5039.114767 \n",
+ "69 5215.482242 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_2 \\\n",
+ "0 0.062923 \n",
+ "1 0.096717 \n",
+ "2 0.164742 \n",
+ "3 0.127015 \n",
+ "4 0.077459 \n",
+ ".. ... \n",
+ "65 0.218248 \n",
+ "66 0.155566 \n",
+ "67 0.125759 \n",
+ "68 0.176246 \n",
+ "69 0.147414 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_3 \\\n",
+ "0 5822.513161 \n",
+ "1 5859.991940 \n",
+ "2 5315.238570 \n",
+ "3 5682.000712 \n",
+ "4 5772.297106 \n",
+ ".. ... \n",
+ "65 5765.002999 \n",
+ "66 5612.968644 \n",
+ "67 5936.846928 \n",
+ "68 5945.292532 \n",
+ "69 5564.663910 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_3 \\\n",
+ "0 0.005925 \n",
+ "1 -0.000473 \n",
+ "2 0.092532 \n",
+ "3 0.029915 \n",
+ "4 0.014499 \n",
+ ".. ... \n",
+ "65 0.057583 \n",
+ "66 0.082437 \n",
+ "67 0.029491 \n",
+ "68 0.028111 \n",
+ "69 0.090333 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_4 \\\n",
+ "0 6037.023411 \n",
+ "1 5977.632024 \n",
+ "2 6000.091002 \n",
+ "3 5921.012439 \n",
+ "4 5861.365272 \n",
+ ".. ... \n",
+ "65 6616.765442 \n",
+ "66 6545.861568 \n",
+ "67 6838.552159 \n",
+ "68 7070.221311 \n",
+ "69 6160.474136 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_4 \\\n",
+ "0 -0.030698 \n",
+ "1 -0.020558 \n",
+ "2 -0.024392 \n",
+ "3 -0.010891 \n",
+ "4 -0.000708 \n",
+ ".. ... \n",
+ "65 -0.081656 \n",
+ "66 -0.070065 \n",
+ "67 -0.117912 \n",
+ "68 -0.155784 \n",
+ "69 -0.007065 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_5 \\\n",
+ "0 5949.756252 \n",
+ "1 5873.903853 \n",
+ "2 5852.535489 \n",
+ "3 5937.907776 \n",
+ "4 5670.640633 \n",
+ ".. ... \n",
+ "65 6540.407431 \n",
+ "66 6227.923582 \n",
+ "67 6813.001549 \n",
+ "68 7064.584402 \n",
+ "69 6270.020011 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_5 \\\n",
+ "0 -0.015799 \n",
+ "1 -0.002848 \n",
+ "2 0.000800 \n",
+ "3 -0.013776 \n",
+ "4 0.031855 \n",
+ ".. ... \n",
+ "65 -0.069174 \n",
+ "66 -0.018091 \n",
+ "67 -0.113735 \n",
+ "68 -0.154862 \n",
+ "69 -0.024973 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_6 \\\n",
+ "0 6223.517883 \n",
+ "1 6192.089129 \n",
+ "2 6006.108852 \n",
+ "3 6191.459971 \n",
+ "4 5949.960467 \n",
+ ".. ... \n",
+ "65 6560.380937 \n",
+ "66 6319.939748 \n",
+ "67 6800.556926 \n",
+ "68 6776.496533 \n",
+ "69 6650.748667 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_6 \\\n",
+ "0 -0.062538 \n",
+ "1 -0.057172 \n",
+ "2 -0.025420 \n",
+ "3 -0.057065 \n",
+ "4 -0.015834 \n",
+ ".. ... \n",
+ "65 -0.072439 \n",
+ "66 -0.033133 \n",
+ "67 -0.111701 \n",
+ "68 -0.107768 \n",
+ "69 -0.087211 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_7 \\\n",
+ "0 6210.989156 \n",
+ "1 6217.811390 \n",
+ "2 6047.176807 \n",
+ "3 6368.673963 \n",
+ "4 6188.619490 \n",
+ ".. ... \n",
+ "65 6541.498076 \n",
+ "66 6328.347984 \n",
+ "67 6317.283208 \n",
+ "68 6499.619097 \n",
+ "69 6412.670943 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_7 \\\n",
+ "0 -0.060399 \n",
+ "1 -0.061564 \n",
+ "2 -0.032431 \n",
+ "3 -0.087320 \n",
+ "4 -0.056580 \n",
+ ".. ... \n",
+ "65 -0.069352 \n",
+ "66 -0.034508 \n",
+ "67 -0.032699 \n",
+ "68 -0.062506 \n",
+ "69 -0.048292 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_8 \\\n",
+ "0 6244.319537 \n",
+ "1 6247.683148 \n",
+ "2 6096.222651 \n",
+ "3 6357.922031 \n",
+ "4 6274.798143 \n",
+ ".. ... \n",
+ "65 6445.427868 \n",
+ "66 6309.849532 \n",
+ "67 6103.421818 \n",
+ "68 6431.116718 \n",
+ "69 6193.253786 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_8 \\\n",
+ "0 -0.066089 \n",
+ "1 -0.066664 \n",
+ "2 -0.040805 \n",
+ "3 -0.085485 \n",
+ "4 -0.071293 \n",
+ ".. ... \n",
+ "65 -0.053647 \n",
+ "66 -0.031484 \n",
+ "67 0.002261 \n",
+ "68 -0.051308 \n",
+ "69 -0.012424 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_9 \\\n",
+ "0 6324.119549 \n",
+ "1 6292.015930 \n",
+ "2 6272.343509 \n",
+ "3 6331.814400 \n",
+ "4 6275.738620 \n",
+ ".. ... \n",
+ "65 6279.188476 \n",
+ "66 6210.926311 \n",
+ "67 6183.841461 \n",
+ "68 6231.886900 \n",
+ "69 6116.982147 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_9 \\\n",
+ "0 -0.079714 \n",
+ "1 -0.074233 \n",
+ "2 -0.070874 \n",
+ "3 -0.081027 \n",
+ "4 -0.071454 \n",
+ ".. ... \n",
+ "65 -0.026472 \n",
+ "66 -0.015313 \n",
+ "67 -0.010885 \n",
+ "68 -0.018739 \n",
+ "69 0.000044 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_10 \\\n",
+ "0 6281.215482 \n",
+ "1 6281.215482 \n",
+ "2 6281.215482 \n",
+ "3 6281.215482 \n",
+ "4 6281.215482 \n",
+ ".. ... \n",
+ "65 6117.889522 \n",
+ "66 6117.889522 \n",
+ "67 6117.889522 \n",
+ "68 6117.889522 \n",
+ "69 6117.889522 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_10 \\\n",
+ "0 -0.072389 \n",
+ "1 -0.072389 \n",
+ "2 -0.072389 \n",
+ "3 -0.072389 \n",
+ "4 -0.072389 \n",
+ ".. ... \n",
+ "65 -0.000104 \n",
+ "66 -0.000104 \n",
+ "67 -0.000104 \n",
+ "68 -0.000104 \n",
+ "69 -0.000104 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_before_ablation \\\n",
+ "0 2541.457199 \n",
+ "1 2541.457199 \n",
+ "2 2541.457199 \n",
+ "3 2541.457199 \n",
+ "4 2541.457199 \n",
+ ".. ... \n",
+ "65 3474.597817 \n",
+ "66 3474.597817 \n",
+ "67 3474.597817 \n",
+ "68 3474.597817 \n",
+ "69 3474.597817 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_before_ablation \\\n",
+ "0 0.566098 \n",
+ "1 0.566098 \n",
+ "2 0.566098 \n",
+ "3 0.566098 \n",
+ "4 0.566098 \n",
+ ".. ... \n",
+ "65 0.432000 \n",
+ "66 0.432000 \n",
+ "67 0.432000 \n",
+ "68 0.432000 \n",
+ "69 0.432000 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_1 \\\n",
+ "0 3573.380509 \n",
+ "1 3598.856442 \n",
+ "2 3376.239077 \n",
+ "3 3427.442019 \n",
+ "4 3503.461554 \n",
+ ".. ... \n",
+ "65 4204.940450 \n",
+ "66 4200.995461 \n",
+ "67 4407.621208 \n",
+ "68 4375.022227 \n",
+ "69 4248.412261 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_1 \\\n",
+ "0 0.389919 \n",
+ "1 0.385569 \n",
+ "2 0.423576 \n",
+ "3 0.414835 \n",
+ "4 0.401856 \n",
+ ".. ... \n",
+ "65 0.312610 \n",
+ "66 0.313255 \n",
+ "67 0.279477 \n",
+ "68 0.284806 \n",
+ "69 0.305503 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_2 \\\n",
+ "0 4710.979622 \n",
+ "1 4652.267727 \n",
+ "2 4407.170549 \n",
+ "3 4648.150206 \n",
+ "4 4715.650971 \n",
+ ".. ... \n",
+ "65 4812.357611 \n",
+ "66 5148.796361 \n",
+ "67 5176.857967 \n",
+ "68 5125.537268 \n",
+ "69 5171.726569 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_2 \\\n",
+ "0 0.195697 \n",
+ "1 0.205721 \n",
+ "2 0.247566 \n",
+ "3 0.206424 \n",
+ "4 0.194899 \n",
+ ".. ... \n",
+ "65 0.213314 \n",
+ "66 0.158316 \n",
+ "67 0.153728 \n",
+ "68 0.162118 \n",
+ "69 0.154567 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_3 \\\n",
+ "0 5465.488800 \n",
+ "1 5453.579322 \n",
+ "2 5038.273900 \n",
+ "3 5345.929388 \n",
+ "4 5419.732700 \n",
+ ".. ... \n",
+ "65 5643.187091 \n",
+ "66 5749.118505 \n",
+ "67 5889.167837 \n",
+ "68 5746.818059 \n",
+ "69 5755.292147 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_3 \\\n",
+ "0 0.066880 \n",
+ "1 0.068913 \n",
+ "2 0.139818 \n",
+ "3 0.087292 \n",
+ "4 0.074692 \n",
+ ".. ... \n",
+ "65 0.077497 \n",
+ "66 0.060180 \n",
+ "67 0.037286 \n",
+ "68 0.060556 \n",
+ "69 0.059171 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_4 \\\n",
+ "0 5856.644776 \n",
+ "1 5852.723797 \n",
+ "2 5544.234938 \n",
+ "3 5749.058984 \n",
+ "4 5622.243735 \n",
+ ".. ... \n",
+ "65 6067.666325 \n",
+ "66 6190.579480 \n",
+ "67 6159.425021 \n",
+ "68 6268.233739 \n",
+ "69 6204.660479 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_4 \\\n",
+ "0 0.000098 \n",
+ "1 0.000768 \n",
+ "2 0.053436 \n",
+ "3 0.018466 \n",
+ "4 0.040117 \n",
+ ".. ... \n",
+ "65 0.008106 \n",
+ "66 -0.011987 \n",
+ "67 -0.006894 \n",
+ "68 -0.024681 \n",
+ "69 -0.014289 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_5 \\\n",
+ "0 5847.537802 \n",
+ "1 5860.980468 \n",
+ "2 5694.140361 \n",
+ "3 5839.309886 \n",
+ "4 5756.416526 \n",
+ ".. ... \n",
+ "65 6125.743285 \n",
+ "66 6151.965930 \n",
+ "67 6183.331053 \n",
+ "68 6296.207000 \n",
+ "69 6181.820292 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_5 \\\n",
+ "0 0.001653 \n",
+ "1 -0.000642 \n",
+ "2 0.027842 \n",
+ "3 0.003058 \n",
+ "4 0.017210 \n",
+ ".. ... \n",
+ "65 -0.001388 \n",
+ "66 -0.005674 \n",
+ "67 -0.010802 \n",
+ "68 -0.029254 \n",
+ "69 -0.010555 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_6 \\\n",
+ "0 5890.341430 \n",
+ "1 5901.633728 \n",
+ "2 5835.593571 \n",
+ "3 5852.236219 \n",
+ "4 5820.147416 \n",
+ ".. ... \n",
+ "65 6196.138333 \n",
+ "66 6235.536408 \n",
+ "67 6178.665567 \n",
+ "68 6385.842720 \n",
+ "69 6215.849342 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_6 \\\n",
+ "0 -0.005655 \n",
+ "1 -0.007583 \n",
+ "2 0.003692 \n",
+ "3 0.000851 \n",
+ "4 0.006329 \n",
+ ".. ... \n",
+ "65 -0.012895 \n",
+ "66 -0.019336 \n",
+ "67 -0.010039 \n",
+ "68 -0.043907 \n",
+ "69 -0.016118 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_7 \\\n",
+ "0 5891.401596 \n",
+ "1 5867.400592 \n",
+ "2 5840.966477 \n",
+ "3 5894.663360 \n",
+ "4 5828.767393 \n",
+ ".. ... \n",
+ "65 6238.070629 \n",
+ "66 6349.831588 \n",
+ "67 6132.201088 \n",
+ "68 6292.629363 \n",
+ "69 6231.571125 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_7 \\\n",
+ "0 -0.005836 \n",
+ "1 -0.001738 \n",
+ "2 0.002775 \n",
+ "3 -0.006393 \n",
+ "4 0.004858 \n",
+ ".. ... \n",
+ "65 -0.019750 \n",
+ "66 -0.038020 \n",
+ "67 -0.002443 \n",
+ "68 -0.028669 \n",
+ "69 -0.018688 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_8 \\\n",
+ "0 5870.056142 \n",
+ "1 5842.365202 \n",
+ "2 5844.553785 \n",
+ "3 5897.950642 \n",
+ "4 5829.349967 \n",
+ ".. ... \n",
+ "65 6324.483467 \n",
+ "66 6324.912346 \n",
+ "67 6152.552330 \n",
+ "68 6221.064362 \n",
+ "69 6159.118213 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_8 \\\n",
+ "0 -0.002192 \n",
+ "1 0.002536 \n",
+ "2 0.002162 \n",
+ "3 -0.006954 \n",
+ "4 0.004758 \n",
+ ".. ... \n",
+ "65 -0.033876 \n",
+ "66 -0.033946 \n",
+ "67 -0.005770 \n",
+ "68 -0.016970 \n",
+ "69 -0.006844 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_9 \\\n",
+ "0 5882.308542 \n",
+ "1 5865.341473 \n",
+ "2 5840.897143 \n",
+ "3 5878.752420 \n",
+ "4 5860.065543 \n",
+ ".. ... \n",
+ "65 6261.602595 \n",
+ "66 6213.181953 \n",
+ "67 6137.879384 \n",
+ "68 6135.388651 \n",
+ "69 6128.387250 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_9 \\\n",
+ "0 -0.004283 \n",
+ "1 -0.001387 \n",
+ "2 0.002787 \n",
+ "3 -0.003676 \n",
+ "4 -0.000486 \n",
+ ".. ... \n",
+ "65 -0.023597 \n",
+ "66 -0.015682 \n",
+ "67 -0.003372 \n",
+ "68 -0.002965 \n",
+ "69 -0.001820 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_10 \\\n",
+ "0 5862.875775 \n",
+ "1 5862.875775 \n",
+ "2 5862.875775 \n",
+ "3 5862.875775 \n",
+ "4 5862.875775 \n",
+ ".. ... \n",
+ "65 6120.715936 \n",
+ "66 6120.715936 \n",
+ "67 6120.715936 \n",
+ "68 6120.715936 \n",
+ "69 6120.715936 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_10 \\\n",
+ "0 -0.000966 \n",
+ "1 -0.000966 \n",
+ "2 -0.000966 \n",
+ "3 -0.000966 \n",
+ "4 -0.000966 \n",
+ ".. ... \n",
+ "65 -0.000566 \n",
+ "66 -0.000566 \n",
+ "67 -0.000566 \n",
+ "68 -0.000566 \n",
+ "69 -0.000566 \n",
+ "\n",
+ " test_subset_ablation_time \\\n",
+ "0 8.213507 \n",
+ "1 8.211402 \n",
+ "2 8.454271 \n",
+ "3 8.288917 \n",
+ "4 8.337007 \n",
+ ".. ... \n",
+ "65 9.552238 \n",
+ "66 9.366884 \n",
+ "67 9.595195 \n",
+ "68 9.291578 \n",
+ "69 9.422463 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_before_ablation_blank \\\n",
+ "0 5880.887238 \n",
+ "1 5880.887238 \n",
+ "2 5880.887238 \n",
+ "3 5880.887238 \n",
+ "4 5880.887238 \n",
+ ".. ... \n",
+ "65 6121.822228 \n",
+ "66 6121.822228 \n",
+ "67 6121.822228 \n",
+ "68 6121.822228 \n",
+ "69 6121.822228 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_before_ablation_blank \\\n",
+ "0 -0.004041 \n",
+ "1 -0.004041 \n",
+ "2 -0.004041 \n",
+ "3 -0.004041 \n",
+ "4 -0.004041 \n",
+ ".. ... \n",
+ "65 -0.000747 \n",
+ "66 -0.000747 \n",
+ "67 -0.000747 \n",
+ "68 -0.000747 \n",
+ "69 -0.000747 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_1_blank \\\n",
+ "0 3912.099558 \n",
+ "1 3959.334316 \n",
+ "2 4289.789706 \n",
+ "3 4146.074898 \n",
+ "4 4016.926503 \n",
+ ".. ... \n",
+ "65 4565.198469 \n",
+ "66 4574.417632 \n",
+ "67 4277.329012 \n",
+ "68 4323.754030 \n",
+ "69 4489.403810 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_1_blank \\\n",
+ "0 0.332089 \n",
+ "1 0.324025 \n",
+ "2 0.267606 \n",
+ "3 0.292143 \n",
+ "4 0.314192 \n",
+ ".. ... \n",
+ "65 0.253718 \n",
+ "66 0.252211 \n",
+ "67 0.300776 \n",
+ "68 0.293187 \n",
+ "69 0.266108 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_2_blank \\\n",
+ "0 3260.557037 \n",
+ "1 3306.352322 \n",
+ "2 3279.532842 \n",
+ "3 3196.169721 \n",
+ "4 3239.020925 \n",
+ ".. ... \n",
+ "65 4202.993784 \n",
+ "66 3941.660325 \n",
+ "67 3914.729195 \n",
+ "68 4059.848931 \n",
+ "69 3884.769653 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_2_blank \\\n",
+ "0 0.443327 \n",
+ "1 0.435508 \n",
+ "2 0.440087 \n",
+ "3 0.454320 \n",
+ "4 0.447004 \n",
+ ".. ... \n",
+ "65 0.312928 \n",
+ "66 0.355649 \n",
+ "67 0.360051 \n",
+ "68 0.336328 \n",
+ "69 0.364949 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_3_blank \\\n",
+ "0 2963.289802 \n",
+ "1 2983.716930 \n",
+ "2 2939.586906 \n",
+ "3 2932.924809 \n",
+ "4 3018.744971 \n",
+ ".. ... \n",
+ "65 3791.454016 \n",
+ "66 3882.135957 \n",
+ "67 3751.300613 \n",
+ "68 3856.213349 \n",
+ "69 3566.339313 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_3_blank \\\n",
+ "0 0.494079 \n",
+ "1 0.490592 \n",
+ "2 0.498126 \n",
+ "3 0.499263 \n",
+ "4 0.484611 \n",
+ ".. ... \n",
+ "65 0.380203 \n",
+ "66 0.365379 \n",
+ "67 0.386767 \n",
+ "68 0.369617 \n",
+ "69 0.417003 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_4_blank \\\n",
+ "0 2835.532455 \n",
+ "1 2762.578581 \n",
+ "2 2790.880643 \n",
+ "3 2779.980132 \n",
+ "4 2833.885025 \n",
+ ".. ... \n",
+ "65 3482.538323 \n",
+ "66 3490.555982 \n",
+ "67 3529.894033 \n",
+ "68 3459.946577 \n",
+ "69 3573.502718 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_4_blank \\\n",
+ "0 0.515891 \n",
+ "1 0.528346 \n",
+ "2 0.523514 \n",
+ "3 0.525375 \n",
+ "4 0.516172 \n",
+ ".. ... \n",
+ "65 0.430702 \n",
+ "66 0.429392 \n",
+ "67 0.422961 \n",
+ "68 0.434395 \n",
+ "69 0.415832 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_5_blank \\\n",
+ "0 2839.168591 \n",
+ "1 2770.645622 \n",
+ "2 2724.115230 \n",
+ "3 2787.119764 \n",
+ "4 2762.022798 \n",
+ ".. ... \n",
+ "65 3517.779677 \n",
+ "66 3537.260652 \n",
+ "67 3488.042689 \n",
+ "68 3542.798313 \n",
+ "69 3729.050354 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_5_blank \\\n",
+ "0 0.515270 \n",
+ "1 0.526969 \n",
+ "2 0.534913 \n",
+ "3 0.524157 \n",
+ "4 0.528441 \n",
+ ".. ... \n",
+ "65 0.424941 \n",
+ "66 0.421757 \n",
+ "67 0.429803 \n",
+ "68 0.420852 \n",
+ "69 0.390405 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_6_blank \\\n",
+ "0 2809.721585 \n",
+ "1 2691.311010 \n",
+ "2 2742.063657 \n",
+ "3 2798.497189 \n",
+ "4 2744.015733 \n",
+ ".. ... \n",
+ "65 3511.064884 \n",
+ "66 3553.312832 \n",
+ "67 3548.661541 \n",
+ "68 3499.935693 \n",
+ "69 3612.189687 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_6_blank \\\n",
+ "0 0.520298 \n",
+ "1 0.540514 \n",
+ "2 0.531849 \n",
+ "3 0.522214 \n",
+ "4 0.531516 \n",
+ ".. ... \n",
+ "65 0.426039 \n",
+ "66 0.419133 \n",
+ "67 0.419893 \n",
+ "68 0.427858 \n",
+ "69 0.409508 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_7_blank \\\n",
+ "0 2729.778409 \n",
+ "1 2688.691704 \n",
+ "2 2696.681777 \n",
+ "3 2728.217519 \n",
+ "4 2727.651489 \n",
+ ".. ... \n",
+ "65 3523.610302 \n",
+ "66 3495.945755 \n",
+ "67 3601.120556 \n",
+ "68 3587.957177 \n",
+ "69 3554.957763 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_7_blank \\\n",
+ "0 0.533946 \n",
+ "1 0.540961 \n",
+ "2 0.539597 \n",
+ "3 0.534213 \n",
+ "4 0.534310 \n",
+ ".. ... \n",
+ "65 0.423988 \n",
+ "66 0.428511 \n",
+ "67 0.411317 \n",
+ "68 0.413469 \n",
+ "69 0.418864 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_8_blank \\\n",
+ "0 2692.894402 \n",
+ "1 2693.598901 \n",
+ "2 2691.911501 \n",
+ "3 2703.871094 \n",
+ "4 2708.425989 \n",
+ ".. ... \n",
+ "65 3475.624613 \n",
+ "66 3496.831801 \n",
+ "67 3560.828284 \n",
+ "68 3584.258787 \n",
+ "69 3565.914084 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_8_blank \\\n",
+ "0 0.540244 \n",
+ "1 0.540123 \n",
+ "2 0.540411 \n",
+ "3 0.538370 \n",
+ "4 0.537592 \n",
+ ".. ... \n",
+ "65 0.431833 \n",
+ "66 0.428366 \n",
+ "67 0.417904 \n",
+ "68 0.414074 \n",
+ "69 0.417073 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_9_blank \\\n",
+ "0 2680.209497 \n",
+ "1 2679.829203 \n",
+ "2 2709.266684 \n",
+ "3 2668.112464 \n",
+ "4 2670.802856 \n",
+ ".. ... \n",
+ "65 3504.931544 \n",
+ "66 3529.774799 \n",
+ "67 3545.626442 \n",
+ "68 3516.033741 \n",
+ "69 3533.556383 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_9_blank \\\n",
+ "0 0.542409 \n",
+ "1 0.542474 \n",
+ "2 0.537448 \n",
+ "3 0.544475 \n",
+ "4 0.544015 \n",
+ ".. ... \n",
+ "65 0.427042 \n",
+ "66 0.422980 \n",
+ "67 0.420389 \n",
+ "68 0.425227 \n",
+ "69 0.422362 \n",
+ "\n",
+ " RF_Regressor_test_subset_MSE_after_ablation_10_blank \\\n",
+ "0 2679.064560 \n",
+ "1 2679.064560 \n",
+ "2 2679.064560 \n",
+ "3 2679.064560 \n",
+ "4 2679.064560 \n",
+ ".. ... \n",
+ "65 3509.831927 \n",
+ "66 3509.831927 \n",
+ "67 3509.831927 \n",
+ "68 3509.831927 \n",
+ "69 3509.831927 \n",
+ "\n",
+ " RF_Regressor_test_subset_R_2_after_ablation_10_blank \\\n",
+ "0 0.542605 \n",
+ "1 0.542605 \n",
+ "2 0.542605 \n",
+ "3 0.542605 \n",
+ "4 0.542605 \n",
+ ".. ... \n",
+ "65 0.426241 \n",
+ "66 0.426241 \n",
+ "67 0.426241 \n",
+ "68 0.426241 \n",
+ "69 0.426241 \n",
+ "\n",
+ " Linear_test_subset_MSE_before_ablation_blank \\\n",
+ "0 5857.395491 \n",
+ "1 5857.395491 \n",
+ "2 5857.395491 \n",
+ "3 5857.395491 \n",
+ "4 5857.395491 \n",
".. ... \n",
- "65 6177.260466 \n",
- "66 6269.951470 \n",
- "67 6141.011126 \n",
- "68 6164.131500 \n",
- "69 6104.946294 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_9 \\\n",
- "0 -0.003973 \n",
- "1 -0.012502 \n",
- "2 -0.011931 \n",
- "3 -0.012633 \n",
- "4 -0.001618 \n",
+ "65 6124.876390 \n",
+ "66 6124.876390 \n",
+ "67 6124.876390 \n",
+ "68 6124.876390 \n",
+ "69 6124.876390 \n",
+ "\n",
+ " Linear_test_subset_R_2_before_ablation_blank \\\n",
+ "0 -0.000030 \n",
+ "1 -0.000030 \n",
+ "2 -0.000030 \n",
+ "3 -0.000030 \n",
+ "4 -0.000030 \n",
".. ... \n",
- "65 -0.012286 \n",
- "66 -0.027476 \n",
- "67 -0.006346 \n",
- "68 -0.010135 \n",
- "69 -0.000436 \n",
- "\n",
- " RF_Plus_Regressor_train_MSE_after_ablation_10 \\\n",
- "0 6032.751362 \n",
- "1 6032.751362 \n",
- "2 6032.751362 \n",
- "3 6032.751362 \n",
- "4 6032.751362 \n",
+ "65 -0.001246 \n",
+ "66 -0.001246 \n",
+ "67 -0.001246 \n",
+ "68 -0.001246 \n",
+ "69 -0.001246 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_1_blank \\\n",
+ "0 3434.906829 \n",
+ "1 3478.443305 \n",
+ "2 3929.424199 \n",
+ "3 3717.936495 \n",
+ "4 3492.276791 \n",
".. ... \n",
- "65 6131.312645 \n",
- "66 6131.312645 \n",
- "67 6131.312645 \n",
- "68 6131.312645 \n",
- "69 6131.312645 \n",
- "\n",
- " RF_Plus_Regressor_train_R_2_after_ablation_10 train_data_ablation_time \\\n",
- "0 -0.000949 10.026768 \n",
- "1 -0.000949 10.083984 \n",
- "2 -0.000949 10.183294 \n",
- "3 -0.000949 9.835077 \n",
- "4 -0.000949 9.809540 \n",
- ".. ... ... \n",
- "65 -0.004756 10.852957 \n",
- "66 -0.004756 10.695844 \n",
- "67 -0.004756 10.828993 \n",
- "68 -0.004756 10.817527 \n",
- "69 -0.004756 10.869999 \n",
- "\n",
- " RF_Regressor_test_MSE_before_ablation \\\n",
- "0 3167.314235 \n",
- "1 3167.314235 \n",
- "2 3167.314235 \n",
- "3 3167.314235 \n",
- "4 3476.788124 \n",
- ".. ... \n",
- "65 3072.457734 \n",
- "66 3072.457734 \n",
- "67 3074.549811 \n",
- "68 3074.549811 \n",
- "69 3074.549811 \n",
+ "65 4533.065114 \n",
+ "66 4525.897079 \n",
+ "67 4181.487573 \n",
+ "68 4178.413687 \n",
+ "69 4415.673403 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_1_blank \\\n",
+ "0 0.413560 \n",
+ "1 0.406127 \n",
+ "2 0.329131 \n",
+ "3 0.365239 \n",
+ "4 0.403765 \n",
+ ".. ... \n",
+ "65 0.258971 \n",
+ "66 0.260142 \n",
+ "67 0.316444 \n",
+ "68 0.316946 \n",
+ "69 0.278161 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_2_blank \\\n",
+ "0 2906.874850 \n",
+ "1 3016.622857 \n",
+ "2 3133.165545 \n",
+ "3 2915.505150 \n",
+ "4 2955.758856 \n",
+ ".. ... \n",
+ "65 4036.250074 \n",
+ "66 3735.627267 \n",
+ "67 3802.852124 \n",
+ "68 3780.783134 \n",
+ "69 3927.760143 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_2_blank \\\n",
+ "0 0.503711 \n",
+ "1 0.484974 \n",
+ "2 0.465076 \n",
+ "3 0.502237 \n",
+ "4 0.495365 \n",
+ ".. ... \n",
+ "65 0.340186 \n",
+ "66 0.389329 \n",
+ "67 0.378340 \n",
+ "68 0.381948 \n",
+ "69 0.357921 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_3_blank \\\n",
+ "0 2776.668307 \n",
+ "1 2817.417330 \n",
+ "2 3011.997732 \n",
+ "3 2825.997755 \n",
+ "4 2686.976279 \n",
+ ".. ... \n",
+ "65 3657.157989 \n",
+ "66 3706.773647 \n",
+ "67 3592.998939 \n",
+ "68 3531.958353 \n",
+ "69 3539.162252 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_3_blank \\\n",
+ "0 0.525941 \n",
+ "1 0.518984 \n",
+ "2 0.485763 \n",
+ "3 0.517519 \n",
+ "4 0.541254 \n",
+ ".. ... \n",
+ "65 0.402157 \n",
+ "66 0.394046 \n",
+ "67 0.412645 \n",
+ "68 0.422624 \n",
+ "69 0.421446 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_4_blank \\\n",
+ "0 3004.535201 \n",
+ "1 2949.727822 \n",
+ "2 3112.891948 \n",
+ "3 3190.456890 \n",
+ "4 2958.235627 \n",
+ ".. ... \n",
+ "65 3432.644180 \n",
+ "66 3391.760003 \n",
+ "67 3269.047589 \n",
+ "68 3439.178531 \n",
+ "69 3418.743202 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_4_blank \\\n",
+ "0 0.487037 \n",
+ "1 0.496395 \n",
+ "2 0.468538 \n",
+ "3 0.455295 \n",
+ "4 0.494942 \n",
+ ".. ... \n",
+ "65 0.438859 \n",
+ "66 0.445542 \n",
+ "67 0.465602 \n",
+ "68 0.437790 \n",
+ "69 0.441131 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_5_blank \\\n",
+ "0 3040.159140 \n",
+ "1 3027.717688 \n",
+ "2 3124.456898 \n",
+ "3 3183.917848 \n",
+ "4 3127.977014 \n",
+ ".. ... \n",
+ "65 3416.521741 \n",
+ "66 3532.284395 \n",
+ "67 3400.390530 \n",
+ "68 3468.716167 \n",
+ "69 3358.897459 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_5_blank \\\n",
+ "0 0.480955 \n",
+ "1 0.483079 \n",
+ "2 0.466563 \n",
+ "3 0.456411 \n",
+ "4 0.465962 \n",
+ ".. ... \n",
+ "65 0.441494 \n",
+ "66 0.422570 \n",
+ "67 0.444131 \n",
+ "68 0.432962 \n",
+ "69 0.450914 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_6_blank \\\n",
+ "0 3226.471955 \n",
+ "1 3171.852993 \n",
+ "2 3230.897294 \n",
+ "3 3062.527867 \n",
+ "4 3240.538911 \n",
+ ".. ... \n",
+ "65 3338.099275 \n",
+ "66 3430.875697 \n",
+ "67 3462.299783 \n",
+ "68 3543.240528 \n",
+ "69 3510.708076 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_6_blank \\\n",
+ "0 0.449146 \n",
+ "1 0.458471 \n",
+ "2 0.448391 \n",
+ "3 0.477136 \n",
+ "4 0.446745 \n",
+ ".. ... \n",
+ "65 0.454314 \n",
+ "66 0.439148 \n",
+ "67 0.434011 \n",
+ "68 0.420779 \n",
+ "69 0.426097 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_7_blank \\\n",
+ "0 3279.136428 \n",
+ "1 2960.568561 \n",
+ "2 3196.423926 \n",
+ "3 3114.178465 \n",
+ "4 2845.779006 \n",
+ ".. ... \n",
+ "65 3401.714814 \n",
+ "66 3452.640648 \n",
+ "67 3561.227406 \n",
+ "68 3573.537624 \n",
+ "69 3617.307137 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_7_blank \\\n",
+ "0 0.440155 \n",
+ "1 0.494544 \n",
+ "2 0.454276 \n",
+ "3 0.468318 \n",
+ "4 0.514142 \n",
+ ".. ... \n",
+ "65 0.443915 \n",
+ "66 0.435590 \n",
+ "67 0.417839 \n",
+ "68 0.415826 \n",
+ "69 0.408671 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_8_blank \\\n",
+ "0 3209.250097 \n",
+ "1 2674.323512 \n",
+ "2 3327.729085 \n",
+ "3 3011.890001 \n",
+ "4 2691.562055 \n",
+ ".. ... \n",
+ "65 3414.243011 \n",
+ "66 3565.410982 \n",
+ "67 3545.027373 \n",
+ "68 3493.357573 \n",
+ "69 3740.467102 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_8_blank \\\n",
+ "0 0.452086 \n",
+ "1 0.543414 \n",
+ "2 0.431859 \n",
+ "3 0.485782 \n",
+ "4 0.540471 \n",
+ ".. ... \n",
+ "65 0.441867 \n",
+ "66 0.417155 \n",
+ "67 0.420487 \n",
+ "68 0.428934 \n",
+ "69 0.388538 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_9_blank \\\n",
+ "0 2989.483161 \n",
+ "1 2693.430849 \n",
+ "2 3111.069912 \n",
+ "3 2927.143396 \n",
+ "4 2656.686546 \n",
+ ".. ... \n",
+ "65 3549.325521 \n",
+ "66 3591.843876 \n",
+ "67 3560.528646 \n",
+ "68 3446.529715 \n",
+ "69 3526.414124 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_9_blank \\\n",
+ "0 0.489607 \n",
+ "1 0.540152 \n",
+ "2 0.468849 \n",
+ "3 0.500250 \n",
+ "4 0.546425 \n",
+ ".. ... \n",
+ "65 0.419785 \n",
+ "66 0.412834 \n",
+ "67 0.417953 \n",
+ "68 0.436589 \n",
+ "69 0.423530 \n",
+ "\n",
+ " Linear_test_subset_MSE_after_ablation_10_blank \\\n",
+ "0 2565.576138 \n",
+ "1 2565.576138 \n",
+ "2 2565.576138 \n",
+ "3 2565.576138 \n",
+ "4 2565.576138 \n",
+ ".. ... \n",
+ "65 3546.190517 \n",
+ "66 3546.190517 \n",
+ "67 3546.190517 \n",
+ "68 3546.190517 \n",
+ "69 3546.190517 \n",
+ "\n",
+ " Linear_test_subset_R_2_after_ablation_10_blank \\\n",
+ "0 0.561981 \n",
+ "1 0.561981 \n",
+ "2 0.561981 \n",
+ "3 0.561981 \n",
+ "4 0.561981 \n",
+ ".. ... \n",
+ "65 0.420297 \n",
+ "66 0.420297 \n",
+ "67 0.420297 \n",
+ "68 0.420297 \n",
+ "69 0.420297 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_before_ablation_blank \\\n",
+ "0 6281.215482 \n",
+ "1 6281.215482 \n",
+ "2 6281.215482 \n",
+ "3 6281.215482 \n",
+ "4 6281.215482 \n",
+ ".. ... \n",
+ "65 6117.889522 \n",
+ "66 6117.889522 \n",
+ "67 6117.889522 \n",
+ "68 6117.889522 \n",
+ "69 6117.889522 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_before_ablation_blank \\\n",
+ "0 -0.072389 \n",
+ "1 -0.072389 \n",
+ "2 -0.072389 \n",
+ "3 -0.072389 \n",
+ "4 -0.072389 \n",
+ ".. ... \n",
+ "65 -0.000104 \n",
+ "66 -0.000104 \n",
+ "67 -0.000104 \n",
+ "68 -0.000104 \n",
+ "69 -0.000104 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_1_blank \\\n",
+ "0 4078.941418 \n",
+ "1 4219.124838 \n",
+ "2 4787.370582 \n",
+ "3 5063.398973 \n",
+ "4 4525.469962 \n",
+ ".. ... \n",
+ "65 4630.301104 \n",
+ "66 4725.567058 \n",
+ "67 4273.624084 \n",
+ "68 4444.060554 \n",
+ "69 4699.814977 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_1_blank \\\n",
+ "0 0.303604 \n",
+ "1 0.279671 \n",
+ "2 0.182655 \n",
+ "3 0.135529 \n",
+ "4 0.227369 \n",
+ ".. ... \n",
+ "65 0.243075 \n",
+ "66 0.227502 \n",
+ "67 0.301382 \n",
+ "68 0.273520 \n",
+ "69 0.231712 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_2_blank \\\n",
+ "0 4141.802429 \n",
+ "1 4408.094032 \n",
+ "2 4180.157570 \n",
+ "3 4167.734211 \n",
+ "4 4331.440232 \n",
+ ".. ... \n",
+ "65 4461.578467 \n",
+ "66 3831.850861 \n",
+ "67 4303.050144 \n",
+ "68 4504.391659 \n",
+ "69 4347.479047 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_2_blank \\\n",
+ "0 0.292872 \n",
+ "1 0.247408 \n",
+ "2 0.286324 \n",
+ "3 0.288445 \n",
+ "4 0.260496 \n",
+ ".. ... \n",
+ "65 0.270657 \n",
+ "66 0.373600 \n",
+ "67 0.296572 \n",
+ "68 0.263658 \n",
+ "69 0.289309 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_3_blank \\\n",
+ "0 4171.239813 \n",
+ "1 4260.803524 \n",
+ "2 4145.383113 \n",
+ "3 4096.191310 \n",
+ "4 4152.517996 \n",
+ ".. ... \n",
+ "65 4086.940877 \n",
+ "66 4110.292001 \n",
+ "67 3672.449170 \n",
+ "68 3900.837880 \n",
+ "69 3463.455559 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_3_blank \\\n",
+ "0 0.287846 \n",
+ "1 0.272555 \n",
+ "2 0.292261 \n",
+ "3 0.300659 \n",
+ "4 0.291043 \n",
+ ".. ... \n",
+ "65 0.331899 \n",
+ "66 0.328082 \n",
+ "67 0.399657 \n",
+ "68 0.362322 \n",
+ "69 0.433822 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_4_blank \\\n",
+ "0 4144.247041 \n",
+ "1 4036.757481 \n",
+ "2 3919.094473 \n",
+ "3 4113.813000 \n",
+ "4 3953.368818 \n",
+ ".. ... \n",
+ "65 3867.554025 \n",
+ "66 3979.834737 \n",
+ "67 3776.282103 \n",
+ "68 3990.586257 \n",
+ "69 3758.003038 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_4_blank \\\n",
+ "0 0.292455 \n",
+ "1 0.310807 \n",
+ "2 0.330895 \n",
+ "3 0.297651 \n",
+ "4 0.325043 \n",
+ ".. ... \n",
+ "65 0.367763 \n",
+ "66 0.349408 \n",
+ "67 0.382683 \n",
+ "68 0.347651 \n",
+ "69 0.385672 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_5_blank \\\n",
+ "0 4009.638211 \n",
+ "1 4051.713547 \n",
+ "2 3995.242224 \n",
+ "3 4134.660106 \n",
+ "4 4132.817470 \n",
+ ".. ... \n",
+ "65 4124.247124 \n",
+ "66 4293.630985 \n",
+ "67 4002.617602 \n",
+ "68 4186.632856 \n",
+ "69 4026.467096 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_5_blank \\\n",
+ "0 0.315437 \n",
+ "1 0.308253 \n",
+ "2 0.317894 \n",
+ "3 0.294092 \n",
+ "4 0.294406 \n",
+ ".. ... \n",
+ "65 0.325801 \n",
+ "66 0.298111 \n",
+ "67 0.345684 \n",
+ "68 0.315603 \n",
+ "69 0.341785 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_6_blank \\\n",
+ "0 3955.399010 \n",
+ "1 3997.748531 \n",
+ "2 3941.916833 \n",
+ "3 4094.226010 \n",
+ "4 4087.757952 \n",
+ ".. ... \n",
+ "65 4247.664086 \n",
+ "66 4481.075995 \n",
+ "67 4119.722671 \n",
+ "68 4288.927715 \n",
+ "69 4151.956487 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_6_blank \\\n",
+ "0 0.324697 \n",
+ "1 0.317467 \n",
+ "2 0.326999 \n",
+ "3 0.300995 \n",
+ "4 0.302099 \n",
+ ".. ... \n",
+ "65 0.305626 \n",
+ "66 0.267469 \n",
+ "67 0.326541 \n",
+ "68 0.298880 \n",
+ "69 0.321271 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_7_blank \\\n",
+ "0 3978.358871 \n",
+ "1 4059.233572 \n",
+ "2 3799.305580 \n",
+ "3 4027.831573 \n",
+ "4 4091.054772 \n",
+ ".. ... \n",
+ "65 4175.739512 \n",
+ "66 4270.511124 \n",
+ "67 4339.266432 \n",
+ "68 4495.201911 \n",
+ "69 4270.034114 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_7_blank \\\n",
+ "0 0.320777 \n",
+ "1 0.306969 \n",
+ "2 0.351347 \n",
+ "3 0.312330 \n",
+ "4 0.301536 \n",
+ ".. ... \n",
+ "65 0.317383 \n",
+ "66 0.301891 \n",
+ "67 0.290651 \n",
+ "68 0.265160 \n",
+ "69 0.301969 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_8_blank \\\n",
+ "0 3902.886409 \n",
+ "1 3948.713206 \n",
+ "2 3577.147009 \n",
+ "3 3914.307020 \n",
+ "4 3889.639927 \n",
+ ".. ... \n",
+ "65 4071.541941 \n",
+ "66 4195.289596 \n",
+ "67 4422.473066 \n",
+ "68 4377.737177 \n",
+ "69 4474.321171 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_8_blank \\\n",
+ "0 0.333662 \n",
+ "1 0.325838 \n",
+ "2 0.389276 \n",
+ "3 0.331712 \n",
+ "4 0.335924 \n",
+ ".. ... \n",
+ "65 0.334417 \n",
+ "66 0.314187 \n",
+ "67 0.277049 \n",
+ "68 0.284362 \n",
+ "69 0.268574 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_9_blank \\\n",
+ "0 3661.068636 \n",
+ "1 3744.098461 \n",
+ "2 3465.659544 \n",
+ "3 3728.641417 \n",
+ "4 3682.165264 \n",
+ ".. ... \n",
+ "65 4087.077584 \n",
+ "66 4229.613224 \n",
+ "67 4409.495930 \n",
+ "68 4291.562443 \n",
+ "69 4369.924399 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_9_blank \\\n",
+ "0 0.374948 \n",
+ "1 0.360772 \n",
+ "2 0.408310 \n",
+ "3 0.363411 \n",
+ "4 0.371346 \n",
+ ".. ... \n",
+ "65 0.331877 \n",
+ "66 0.308576 \n",
+ "67 0.279171 \n",
+ "68 0.298450 \n",
+ "69 0.285640 \n",
+ "\n",
+ " XGB_Regressor_test_subset_MSE_after_ablation_10_blank \\\n",
+ "0 3557.841426 \n",
+ "1 3557.841426 \n",
+ "2 3557.841426 \n",
+ "3 3557.841426 \n",
+ "4 3557.841426 \n",
+ ".. ... \n",
+ "65 4204.805826 \n",
+ "66 4204.805826 \n",
+ "67 4204.805826 \n",
+ "68 4204.805826 \n",
+ "69 4204.805826 \n",
+ "\n",
+ " XGB_Regressor_test_subset_R_2_after_ablation_10_blank \\\n",
+ "0 0.392572 \n",
+ "1 0.392572 \n",
+ "2 0.392572 \n",
+ "3 0.392572 \n",
+ "4 0.392572 \n",
+ ".. ... \n",
+ "65 0.312632 \n",
+ "66 0.312632 \n",
+ "67 0.312632 \n",
+ "68 0.312632 \n",
+ "69 0.312632 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_before_ablation_blank \\\n",
+ "0 5862.016707 \n",
+ "1 5862.016707 \n",
+ "2 5862.016707 \n",
+ "3 5862.016707 \n",
+ "4 5862.016707 \n",
+ ".. ... \n",
+ "65 6118.188308 \n",
+ "66 6118.188308 \n",
+ "67 6118.188308 \n",
+ "68 6118.188308 \n",
+ "69 6118.188308 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_before_ablation_blank \\\n",
+ "0 -0.000819 \n",
+ "1 -0.000819 \n",
+ "2 -0.000819 \n",
+ "3 -0.000819 \n",
+ "4 -0.000819 \n",
+ ".. ... \n",
+ "65 -0.000153 \n",
+ "66 -0.000153 \n",
+ "67 -0.000153 \n",
+ "68 -0.000153 \n",
+ "69 -0.000153 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_1_blank \\\n",
+ "0 3776.067195 \n",
+ "1 3792.229582 \n",
+ "2 4157.290029 \n",
+ "3 4012.823317 \n",
+ "4 3840.160816 \n",
+ ".. ... \n",
+ "65 4554.336197 \n",
+ "66 4570.576428 \n",
+ "67 4312.856796 \n",
+ "68 4347.438699 \n",
+ "69 4473.629476 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_1_blank \\\n",
+ "0 0.355314 \n",
+ "1 0.352555 \n",
+ "2 0.290228 \n",
+ "3 0.314893 \n",
+ "4 0.344371 \n",
+ ".. ... \n",
+ "65 0.255493 \n",
+ "66 0.252839 \n",
+ "67 0.294968 \n",
+ "68 0.289315 \n",
+ "69 0.268687 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_2_blank \\\n",
+ "0 3002.695954 \n",
+ "1 3092.988693 \n",
+ "2 3194.473744 \n",
+ "3 3056.976176 \n",
+ "4 3031.188396 \n",
+ ".. ... \n",
+ "65 4087.341630 \n",
+ "66 3806.828252 \n",
+ "67 3869.397091 \n",
+ "68 3913.814050 \n",
+ "69 3891.952087 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_2_blank \\\n",
+ "0 0.487351 \n",
+ "1 0.471936 \n",
+ "2 0.454609 \n",
+ "3 0.478084 \n",
+ "4 0.482487 \n",
+ ".. ... \n",
+ "65 0.331834 \n",
+ "66 0.377690 \n",
+ "67 0.367462 \n",
+ "68 0.360201 \n",
+ "69 0.363775 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_3_blank \\\n",
+ "0 2704.167022 \n",
+ "1 2733.015815 \n",
+ "2 2930.804827 \n",
+ "3 2770.118982 \n",
+ "4 2722.696131 \n",
+ ".. ... \n",
+ "65 3669.516753 \n",
+ "66 3759.608774 \n",
+ "67 3620.284900 \n",
+ "68 3635.666334 \n",
+ "69 3520.269715 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_3_blank \\\n",
+ "0 0.538319 \n",
+ "1 0.533394 \n",
+ "2 0.499625 \n",
+ "3 0.527059 \n",
+ "4 0.535156 \n",
+ ".. ... \n",
+ "65 0.400137 \n",
+ "66 0.385409 \n",
+ "67 0.408185 \n",
+ "68 0.405670 \n",
+ "69 0.424534 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_4_blank \\\n",
+ "0 2643.172114 \n",
+ "1 2564.054141 \n",
+ "2 2757.229952 \n",
+ "3 2700.222694 \n",
+ "4 2616.745973 \n",
+ ".. ... \n",
+ "65 3467.364448 \n",
+ "66 3408.515859 \n",
+ "67 3385.419843 \n",
+ "68 3362.368505 \n",
+ "69 3479.444407 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_4_blank \\\n",
+ "0 0.548733 \n",
+ "1 0.562240 \n",
+ "2 0.529260 \n",
+ "3 0.538992 \n",
+ "4 0.553244 \n",
+ ".. ... \n",
+ "65 0.433183 \n",
+ "66 0.442803 \n",
+ "67 0.446578 \n",
+ "68 0.450347 \n",
+ "69 0.431208 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_5_blank \\\n",
+ "0 2667.464939 \n",
+ "1 2610.994432 \n",
+ "2 2661.353767 \n",
+ "3 2668.229263 \n",
+ "4 2595.289374 \n",
+ ".. ... \n",
+ "65 3470.756627 \n",
+ "66 3486.048868 \n",
+ "67 3373.235561 \n",
+ "68 3401.274428 \n",
+ "69 3549.656569 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_5_blank \\\n",
+ "0 0.544585 \n",
+ "1 0.554226 \n",
+ "2 0.545628 \n",
+ "3 0.544455 \n",
+ "4 0.556908 \n",
+ ".. ... \n",
+ "65 0.432628 \n",
+ "66 0.430128 \n",
+ "67 0.448570 \n",
+ "68 0.443987 \n",
+ "69 0.419730 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_6_blank \\\n",
+ "0 2642.388141 \n",
+ "1 2564.381955 \n",
+ "2 2640.533322 \n",
+ "3 2641.775898 \n",
+ "4 2591.050321 \n",
+ ".. ... \n",
+ "65 3426.308046 \n",
+ "66 3447.239195 \n",
+ "67 3434.690834 \n",
+ "68 3406.397571 \n",
+ "69 3526.783158 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_6_blank \\\n",
+ "0 0.548866 \n",
+ "1 0.562184 \n",
+ "2 0.549183 \n",
+ "3 0.548971 \n",
+ "4 0.557631 \n",
+ ".. ... \n",
+ "65 0.439894 \n",
+ "66 0.436473 \n",
+ "67 0.438524 \n",
+ "68 0.443149 \n",
+ "69 0.423470 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_7_blank \\\n",
+ "0 2565.443158 \n",
+ "1 2551.563643 \n",
+ "2 2592.707466 \n",
+ "3 2591.837752 \n",
+ "4 2568.578591 \n",
+ ".. ... \n",
+ "65 3422.427748 \n",
+ "66 3399.367759 \n",
+ "67 3497.877026 \n",
+ "68 3497.782692 \n",
+ "69 3512.839878 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_7_blank \\\n",
+ "0 0.562003 \n",
+ "1 0.564373 \n",
+ "2 0.557348 \n",
+ "3 0.557497 \n",
+ "4 0.561468 \n",
+ ".. ... \n",
+ "65 0.440529 \n",
+ "66 0.444298 \n",
+ "67 0.428195 \n",
+ "68 0.428210 \n",
+ "69 0.425749 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_8_blank \\\n",
+ "0 2541.553235 \n",
+ "1 2545.713079 \n",
+ "2 2560.398985 \n",
+ "3 2564.562730 \n",
+ "4 2566.086550 \n",
+ ".. ... \n",
+ "65 3367.681185 \n",
+ "66 3438.643309 \n",
+ "67 3478.243780 \n",
+ "68 3490.790081 \n",
+ "69 3524.189811 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_8_blank \\\n",
+ "0 0.566082 \n",
+ "1 0.565372 \n",
+ "2 0.562864 \n",
+ "3 0.562154 \n",
+ "4 0.561893 \n",
+ ".. ... \n",
+ "65 0.449478 \n",
+ "66 0.437878 \n",
+ "67 0.431404 \n",
+ "68 0.429353 \n",
+ "69 0.423893 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_9_blank \\\n",
+ "0 2544.841992 \n",
+ "1 2541.588137 \n",
+ "2 2567.722606 \n",
+ "3 2554.271693 \n",
+ "4 2533.869882 \n",
+ ".. ... \n",
+ "65 3398.510612 \n",
+ "66 3461.606999 \n",
+ "67 3488.432591 \n",
+ "68 3473.687224 \n",
+ "69 3486.336515 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_9_blank \\\n",
+ "0 0.565520 \n",
+ "1 0.566076 \n",
+ "2 0.561614 \n",
+ "3 0.563911 \n",
+ "4 0.567394 \n",
+ ".. ... \n",
+ "65 0.444439 \n",
+ "66 0.434124 \n",
+ "67 0.429739 \n",
+ "68 0.432149 \n",
+ "69 0.430081 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_MSE_after_ablation_10_blank \\\n",
+ "0 2541.457199 \n",
+ "1 2541.457199 \n",
+ "2 2541.457199 \n",
+ "3 2541.457199 \n",
+ "4 2541.457199 \n",
+ ".. ... \n",
+ "65 3474.597817 \n",
+ "66 3474.597817 \n",
+ "67 3474.597817 \n",
+ "68 3474.597817 \n",
+ "69 3474.597817 \n",
+ "\n",
+ " RF_Plus_Regressor_test_subset_R_2_after_ablation_10_blank \\\n",
+ "0 0.566098 \n",
+ "1 0.566098 \n",
+ "2 0.566098 \n",
+ "3 0.566098 \n",
+ "4 0.566098 \n",
+ ".. ... \n",
+ "65 0.432000 \n",
+ "66 0.432000 \n",
+ "67 0.432000 \n",
+ "68 0.432000 \n",
+ "69 0.432000 \n",
+ "\n",
+ " test_subset_blank_ablation_time RF_Regressor_test_MSE_before_ablation \\\n",
+ "0 8.630264 2640.499813 \n",
+ "1 8.487405 2640.499813 \n",
+ "2 8.591958 2640.499813 \n",
+ "3 8.565224 2640.499813 \n",
+ "4 8.649657 NaN \n",
+ ".. ... ... \n",
+ "65 9.641644 3317.655397 \n",
+ "66 9.647025 3317.655397 \n",
+ "67 10.038960 NaN \n",
+ "68 9.786609 3317.655397 \n",
+ "69 9.847889 NaN \n",
"\n",
" RF_Regressor_test_R_2_before_ablation \\\n",
- "0 0.445492 \n",
- "1 0.445492 \n",
- "2 0.445492 \n",
- "3 0.445492 \n",
- "4 0.417422 \n",
+ "0 0.535380 \n",
+ "1 0.535380 \n",
+ "2 0.535380 \n",
+ "3 0.535380 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.448450 \n",
- "66 0.448450 \n",
- "67 0.439991 \n",
- "68 0.439991 \n",
- "69 0.439991 \n",
+ "65 0.470632 \n",
+ "66 0.470632 \n",
+ "67 NaN \n",
+ "68 0.470632 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_1 \\\n",
- "0 3788.003075 \n",
- "1 3827.691114 \n",
- "2 3911.846966 \n",
- "3 3775.838507 \n",
- "4 4194.571341 \n",
+ "0 3524.835070 \n",
+ "1 3571.052791 \n",
+ "2 3519.122896 \n",
+ "3 3522.753563 \n",
+ "4 NaN \n",
".. ... \n",
- "65 3599.197638 \n",
- "66 3743.320860 \n",
- "67 3824.972040 \n",
- "68 3677.383895 \n",
- "69 3488.988909 \n",
+ "65 4252.098901 \n",
+ "66 4151.837191 \n",
+ "67 NaN \n",
+ "68 4147.385047 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_1 \\\n",
- "0 0.336827 \n",
- "1 0.329878 \n",
- "2 0.315145 \n",
- "3 0.338956 \n",
- "4 0.297148 \n",
+ "0 0.379773 \n",
+ "1 0.371641 \n",
+ "2 0.380779 \n",
+ "3 0.380140 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.353892 \n",
- "66 0.328020 \n",
- "67 0.303307 \n",
- "68 0.330189 \n",
- "69 0.364504 \n",
+ "65 0.321531 \n",
+ "66 0.337529 \n",
+ "67 NaN \n",
+ "68 0.338239 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_2 \\\n",
- "0 4752.063649 \n",
- "1 4578.262051 \n",
- "2 4673.293043 \n",
- "3 4633.157541 \n",
- "4 5334.974847 \n",
+ "0 4339.761162 \n",
+ "1 4318.344175 \n",
+ "2 4341.295617 \n",
+ "3 4492.754726 \n",
+ "4 NaN \n",
".. ... \n",
- "65 4064.045641 \n",
- "66 4211.329333 \n",
- "67 4273.545813 \n",
- "68 4223.973426 \n",
- "69 4038.189629 \n",
+ "65 4965.848450 \n",
+ "66 5163.578466 \n",
+ "67 NaN \n",
+ "68 4987.539777 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_2 \\\n",
- "0 0.168047 \n",
- "1 0.198474 \n",
- "2 0.181837 \n",
- "3 0.188864 \n",
- "4 0.106060 \n",
+ "0 0.236380 \n",
+ "1 0.240148 \n",
+ "2 0.236110 \n",
+ "3 0.209459 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.270445 \n",
- "66 0.244006 \n",
- "67 0.221602 \n",
- "68 0.230631 \n",
- "69 0.264471 \n",
+ "65 0.207644 \n",
+ "66 0.176094 \n",
+ "67 NaN \n",
+ "68 0.204183 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_3 \\\n",
- "0 5282.813050 \n",
- "1 5044.353110 \n",
- "2 5165.809068 \n",
- "3 5247.502613 \n",
- "4 5596.675389 \n",
+ "0 5044.129946 \n",
+ "1 5017.600255 \n",
+ "2 5080.619597 \n",
+ "3 5250.687945 \n",
+ "4 NaN \n",
".. ... \n",
- "65 4786.645423 \n",
- "66 4765.872128 \n",
- "67 4822.571646 \n",
- "68 4853.249242 \n",
- "69 4713.345462 \n",
+ "65 5733.329545 \n",
+ "66 5923.044278 \n",
+ "67 NaN \n",
+ "68 5932.927451 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_3 \\\n",
- "0 0.075127 \n",
- "1 0.116875 \n",
- "2 0.095611 \n",
- "3 0.081309 \n",
- "4 0.062209 \n",
+ "0 0.112440 \n",
+ "1 0.117108 \n",
+ "2 0.106019 \n",
+ "3 0.076094 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.140728 \n",
- "66 0.144457 \n",
- "67 0.121601 \n",
- "68 0.116013 \n",
- "69 0.141496 \n",
+ "65 0.085184 \n",
+ "66 0.054913 \n",
+ "67 NaN \n",
+ "68 0.053336 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_4 \\\n",
- "0 5661.928879 \n",
- "1 5456.091373 \n",
- "2 5579.673507 \n",
- "3 5637.322633 \n",
- "4 5937.622020 \n",
+ "0 5423.189116 \n",
+ "1 5441.462496 \n",
+ "2 5361.659892 \n",
+ "3 5540.180309 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5216.701738 \n",
- "66 5236.877977 \n",
- "67 5169.557621 \n",
- "68 5184.298032 \n",
- "69 5046.789311 \n",
+ "65 6078.686174 \n",
+ "66 6195.837162 \n",
+ "67 NaN \n",
+ "68 6292.487953 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_4 \\\n",
- "0 0.008755 \n",
- "1 0.044791 \n",
- "2 0.023155 \n",
- "3 0.013063 \n",
- "4 0.005079 \n",
+ "0 0.045741 \n",
+ "1 0.042526 \n",
+ "2 0.056568 \n",
+ "3 0.025155 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.063527 \n",
- "66 0.059905 \n",
- "67 0.058400 \n",
- "68 0.055715 \n",
- "69 0.080761 \n",
+ "65 0.030079 \n",
+ "66 0.011386 \n",
+ "67 NaN \n",
+ "68 -0.004036 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_5 \\\n",
- "0 5833.559426 \n",
- "1 5793.795173 \n",
- "2 5866.425027 \n",
- "3 5960.763458 \n",
- "4 6111.152277 \n",
+ "0 5559.160140 \n",
+ "1 5578.882603 \n",
+ "2 5543.610178 \n",
+ "3 5643.169395 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5425.473666 \n",
- "66 5625.037238 \n",
- "67 5364.977537 \n",
- "68 5471.391949 \n",
- "69 5304.597975 \n",
+ "65 6173.750086 \n",
+ "66 6172.416916 \n",
+ "67 NaN \n",
+ "68 6302.699742 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_5 \\\n",
- "0 -0.021293 \n",
- "1 -0.014331 \n",
- "2 -0.027047 \n",
- "3 -0.043563 \n",
- "4 -0.023998 \n",
+ "0 0.021816 \n",
+ "1 0.018345 \n",
+ "2 0.024552 \n",
+ "3 0.007033 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.026049 \n",
- "66 -0.009775 \n",
- "67 0.022805 \n",
- "68 0.003422 \n",
- "69 0.033803 \n",
+ "65 0.014910 \n",
+ "66 0.015123 \n",
+ "67 NaN \n",
+ "68 -0.005665 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_6 \\\n",
- "0 5865.509482 \n",
- "1 6010.746038 \n",
- "2 5899.293811 \n",
- "3 5977.057139 \n",
- "4 6143.624744 \n",
+ "0 5558.547528 \n",
+ "1 5657.157261 \n",
+ "2 5603.054347 \n",
+ "3 5570.930650 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5590.326152 \n",
- "66 5521.985960 \n",
- "67 5362.147595 \n",
- "68 5443.474923 \n",
- "69 5388.787525 \n",
+ "65 6142.718017 \n",
+ "66 6267.709333 \n",
+ "67 NaN \n",
+ "68 6448.386612 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_6 \\\n",
- "0 -0.026887 \n",
- "1 -0.052313 \n",
- "2 -0.032801 \n",
- "3 -0.046415 \n",
- "4 -0.029439 \n",
+ "0 0.021923 \n",
+ "1 0.004572 \n",
+ "2 0.014092 \n",
+ "3 0.019744 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.003544 \n",
- "66 0.008724 \n",
- "67 0.023321 \n",
- "68 0.008507 \n",
- "69 0.018468 \n",
+ "65 0.019862 \n",
+ "66 -0.000082 \n",
+ "67 NaN \n",
+ "68 -0.028911 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_7 \\\n",
- "0 5966.941781 \n",
- "1 6049.385658 \n",
- "2 6021.113226 \n",
- "3 6028.927315 \n",
- "4 6163.867887 \n",
+ "0 5620.116672 \n",
+ "1 5614.647017 \n",
+ "2 5646.812614 \n",
+ "3 5662.431118 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5562.124282 \n",
- "66 5545.446533 \n",
- "67 5383.491593 \n",
- "68 5455.547129 \n",
- "69 5465.219576 \n",
+ "65 6271.061133 \n",
+ "66 6357.712212 \n",
+ "67 NaN \n",
+ "68 6412.611071 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_7 \\\n",
- "0 -0.044645 \n",
- "1 -0.059078 \n",
- "2 -0.054128 \n",
- "3 -0.055496 \n",
- "4 -0.032831 \n",
+ "0 0.011090 \n",
+ "1 0.012052 \n",
+ "2 0.006392 \n",
+ "3 0.003644 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.001518 \n",
- "66 0.004512 \n",
- "67 0.019433 \n",
- "68 0.006308 \n",
- "69 0.004547 \n",
+ "65 -0.000617 \n",
+ "66 -0.014443 \n",
+ "67 NaN \n",
+ "68 -0.023203 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_8 \\\n",
- "0 6001.779722 \n",
- "1 5998.481445 \n",
- "2 6042.816515 \n",
- "3 6074.807174 \n",
- "4 6244.000528 \n",
+ "0 5710.918759 \n",
+ "1 5705.335037 \n",
+ "2 5742.659997 \n",
+ "3 5773.100746 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5644.709360 \n",
- "66 5653.778023 \n",
- "67 5405.576376 \n",
- "68 5499.562086 \n",
- "69 5509.129123 \n",
+ "65 6362.782912 \n",
+ "66 6342.834816 \n",
+ "67 NaN \n",
+ "68 6337.685910 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_8 \\\n",
- "0 -0.050744 \n",
- "1 -0.050166 \n",
- "2 -0.057928 \n",
- "3 -0.063529 \n",
- "4 -0.046258 \n",
+ "0 -0.004888 \n",
+ "1 -0.003905 \n",
+ "2 -0.010473 \n",
+ "3 -0.015829 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.013307 \n",
- "66 -0.014935 \n",
- "67 0.015410 \n",
- "68 -0.001709 \n",
- "69 -0.003451 \n",
+ "65 -0.015252 \n",
+ "66 -0.012069 \n",
+ "67 NaN \n",
+ "68 -0.011247 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_9 \\\n",
- "0 6030.147576 \n",
- "1 6036.697699 \n",
- "2 6017.320805 \n",
- "3 6086.136079 \n",
- "4 6396.107074 \n",
+ "0 5776.883880 \n",
+ "1 5783.179625 \n",
+ "2 5778.819764 \n",
+ "3 5796.952295 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5619.576540 \n",
- "66 5661.451333 \n",
- "67 5547.677265 \n",
- "68 5564.283426 \n",
- "69 5521.703510 \n",
+ "65 6344.548400 \n",
+ "66 6322.005677 \n",
+ "67 NaN \n",
+ "68 6278.027761 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_9 \\\n",
- "0 -0.055710 \n",
- "1 -0.056857 \n",
- "2 -0.053464 \n",
- "3 -0.065512 \n",
- "4 -0.071746 \n",
+ "0 -0.016495 \n",
+ "1 -0.017603 \n",
+ "2 -0.016836 \n",
+ "3 -0.020026 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.008795 \n",
- "66 -0.016312 \n",
- "67 -0.010472 \n",
- "68 -0.013497 \n",
- "69 -0.005741 \n",
+ "65 -0.012342 \n",
+ "66 -0.008745 \n",
+ "67 NaN \n",
+ "68 -0.001728 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_MSE_after_ablation_10 \\\n",
- "0 6067.018319 \n",
- "1 6067.018319 \n",
- "2 6067.018319 \n",
- "3 6067.018319 \n",
- "4 6465.545412 \n",
+ "0 5801.671997 \n",
+ "1 5801.671997 \n",
+ "2 5801.671997 \n",
+ "3 5801.671997 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5664.609603 \n",
- "66 5664.609603 \n",
- "67 5648.814576 \n",
- "68 5648.814576 \n",
- "69 5648.814576 \n",
+ "65 6286.679067 \n",
+ "66 6286.679067 \n",
+ "67 NaN \n",
+ "68 6286.679067 \n",
+ "69 NaN \n",
"\n",
" RF_Regressor_test_R_2_after_ablation_10 Linear_test_MSE_before_ablation \\\n",
- "0 -0.062165 3121.854972 \n",
- "1 -0.062165 3121.854972 \n",
- "2 -0.062165 3121.854972 \n",
- "3 -0.062165 3121.854972 \n",
- "4 -0.083381 3465.585233 \n",
+ "0 -0.020857 2496.785106 \n",
+ "1 -0.020857 2496.785106 \n",
+ "2 -0.020857 2496.785106 \n",
+ "3 -0.020857 2496.785106 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.016879 3213.858553 \n",
- "66 -0.016879 3213.858553 \n",
- "67 -0.028894 3438.229965 \n",
- "68 -0.028894 3438.229965 \n",
- "69 -0.028894 3438.229965 \n",
+ "65 -0.003109 3332.826395 \n",
+ "66 -0.003109 3332.826395 \n",
+ "67 NaN NaN \n",
+ "68 -0.003109 3332.826395 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_before_ablation Linear_test_MSE_after_ablation_1 \\\n",
- "0 0.453451 3802.338138 \n",
- "1 0.453451 3803.232973 \n",
- "2 0.453451 3782.799439 \n",
- "3 0.453451 3739.288445 \n",
- "4 0.419299 4161.596525 \n",
+ "0 0.560668 3933.440887 \n",
+ "1 0.560668 3940.612956 \n",
+ "2 0.560668 3747.641792 \n",
+ "3 0.560668 3874.602772 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 0.423066 4037.406723 \n",
- "66 0.423066 4218.066221 \n",
- "67 0.373749 4269.577351 \n",
- "68 0.373749 4250.446715 \n",
- "69 0.373749 4154.543994 \n",
+ "65 0.468211 4372.466149 \n",
+ "66 0.468211 4252.332749 \n",
+ "67 NaN NaN \n",
+ "68 0.468211 4359.423484 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_1 Linear_test_MSE_after_ablation_2 \\\n",
- "0 0.334317 4944.247196 \n",
- "1 0.334160 4703.872125 \n",
- "2 0.337738 4640.935068 \n",
- "3 0.345355 4678.676433 \n",
- "4 0.302674 5338.566511 \n",
+ "0 0.307876 5378.186635 \n",
+ "1 0.306614 5335.869899 \n",
+ "2 0.340569 4896.166926 \n",
+ "3 0.318229 5195.998249 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 0.275227 5200.381743 \n",
- "66 0.242796 5356.336721 \n",
- "67 0.222325 5222.916628 \n",
- "68 0.225809 5168.535770 \n",
- "69 0.243278 5271.242084 \n",
+ "65 0.302325 5200.909978 \n",
+ "66 0.321494 5500.769377 \n",
+ "67 NaN NaN \n",
+ "68 0.304406 5585.910286 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_2 Linear_test_MSE_after_ablation_3 \\\n",
- "0 0.134401 5658.191138 \n",
- "1 0.176484 5324.761627 \n",
- "2 0.187502 5146.024758 \n",
- "3 0.180895 5452.652247 \n",
- "4 0.105458 5866.474772 \n",
+ "0 0.053660 6372.090383 \n",
+ "1 0.061106 6327.986356 \n",
+ "2 0.138475 5638.775425 \n",
+ "3 0.085717 6136.557906 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 0.066456 5884.153057 \n",
- "66 0.038460 5997.063026 \n",
- "67 0.048681 5812.610512 \n",
- "68 0.058586 5904.704003 \n",
- "69 0.039878 5923.989444 \n",
+ "65 0.170138 6249.120862 \n",
+ "66 0.122292 6499.331943 \n",
+ "67 NaN NaN \n",
+ "68 0.108707 6615.984755 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_3 Linear_test_MSE_after_ablation_4 \\\n",
- "0 0.009409 6066.312661 \n",
- "1 0.067783 5773.709727 \n",
- "2 0.099075 5560.543096 \n",
- "3 0.045393 5808.699092 \n",
- "4 0.017001 6058.949364 \n",
+ "0 -0.121227 6771.155629 \n",
+ "1 -0.113466 6817.218702 \n",
+ "2 0.007807 6298.362961 \n",
+ "3 -0.079783 6674.583225 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.056290 6556.102398 \n",
- "66 -0.076559 6524.414652 \n",
- "67 -0.058728 6323.222346 \n",
- "68 -0.075502 6346.397918 \n",
- "69 -0.079015 6127.787889 \n",
+ "65 0.002884 6895.247992 \n",
+ "66 -0.037040 7017.833958 \n",
+ "67 NaN NaN \n",
+ "68 -0.055653 7217.577286 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_4 Linear_test_MSE_after_ablation_5 \\\n",
- "0 -0.062042 6021.472063 \n",
- "1 -0.010815 5977.826552 \n",
- "2 0.026504 5746.434317 \n",
- "3 -0.016941 6069.614343 \n",
- "4 -0.015251 6186.505044 \n",
+ "0 -0.191446 7068.389560 \n",
+ "1 -0.199551 6960.960204 \n",
+ "2 -0.108254 6810.017866 \n",
+ "3 -0.174453 6842.073247 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.176915 6885.746921 \n",
- "66 -0.171227 7015.708280 \n",
- "67 -0.151733 6789.017275 \n",
- "68 -0.155954 6559.339739 \n",
- "69 -0.116136 6595.262987 \n",
+ "65 -0.100213 7031.352831 \n",
+ "66 -0.119772 6999.075380 \n",
+ "67 NaN NaN \n",
+ "68 -0.151644 7214.779536 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_5 Linear_test_MSE_after_ablation_6 \\\n",
- "0 -0.054191 6101.326312 \n",
- "1 -0.046550 5986.809965 \n",
- "2 -0.006040 5832.336892 \n",
- "3 -0.062620 5915.356963 \n",
- "4 -0.036624 6078.148133 \n",
+ "0 -0.243747 7447.880628 \n",
+ "1 -0.224844 7284.148792 \n",
+ "2 -0.198284 7304.802884 \n",
+ "3 -0.203925 7189.118672 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.236091 6917.122114 \n",
- "66 -0.259421 7106.531998 \n",
- "67 -0.236574 6888.956923 \n",
- "68 -0.194740 6702.852473 \n",
- "69 -0.201283 6947.470195 \n",
+ "65 -0.121930 6866.904602 \n",
+ "66 -0.116779 7064.166452 \n",
+ "67 NaN NaN \n",
+ "68 -0.151197 7129.172211 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_6 Linear_test_MSE_after_ablation_7 \\\n",
- "0 -0.068172 6090.259226 \n",
- "1 -0.048123 5983.111169 \n",
- "2 -0.021079 5952.085807 \n",
- "3 -0.035613 6006.034824 \n",
- "4 -0.018468 6079.932688 \n",
+ "0 -0.310522 7634.217290 \n",
+ "1 -0.281712 7264.408403 \n",
+ "2 -0.285346 7688.411155 \n",
+ "3 -0.264990 7566.606181 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.241723 6905.819125 \n",
- "66 -0.275725 6990.755293 \n",
- "67 -0.254778 6342.579611 \n",
- "68 -0.220880 6652.209705 \n",
- "69 -0.265435 6558.722886 \n",
+ "65 -0.095690 6825.980328 \n",
+ "66 -0.127165 7161.699581 \n",
+ "67 NaN NaN \n",
+ "68 -0.137538 6905.484625 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_7 Linear_test_MSE_after_ablation_8 \\\n",
- "0 -0.066234 6039.050269 \n",
- "1 -0.047475 5939.508997 \n",
- "2 -0.042044 5999.332220 \n",
- "3 -0.051489 5993.584111 \n",
- "4 -0.018767 6124.462336 \n",
+ "0 -0.343309 7542.656034 \n",
+ "1 -0.278238 6351.745669 \n",
+ "2 -0.352845 7574.919172 \n",
+ "3 -0.331413 7716.289158 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.239694 6489.716483 \n",
- "66 -0.254941 6853.979093 \n",
- "67 -0.155259 5805.435651 \n",
- "68 -0.211656 6360.483378 \n",
- "69 -0.194628 6060.428514 \n",
+ "65 -0.089160 6716.099781 \n",
+ "66 -0.142728 7016.127259 \n",
+ "67 NaN NaN \n",
+ "68 -0.101846 6732.551850 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_8 Linear_test_MSE_after_ablation_9 \\\n",
- "0 -0.057269 5875.871694 \n",
- "1 -0.039842 5810.251492 \n",
- "2 -0.050315 5843.222894 \n",
- "3 -0.049309 5835.219347 \n",
- "4 -0.026228 6098.814817 \n",
+ "0 -0.327198 6778.699347 \n",
+ "1 -0.117647 5868.856530 \n",
+ "2 -0.332875 6629.814159 \n",
+ "3 -0.357751 6944.478731 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.164998 5999.861947 \n",
- "66 -0.230388 6484.153190 \n",
- "67 -0.057421 5647.333250 \n",
- "68 -0.158520 5807.268863 \n",
- "69 -0.103867 5729.046317 \n",
+ "65 -0.071627 6500.228772 \n",
+ "66 -0.119500 6654.176147 \n",
+ "67 NaN NaN \n",
+ "68 -0.074253 6519.281447 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_9 Linear_test_MSE_after_ablation_10 \\\n",
- "0 -0.028701 5743.289993 \n",
- "1 -0.017212 5743.289993 \n",
- "2 -0.022985 5743.289993 \n",
- "3 -0.021584 5743.289993 \n",
- "4 -0.021931 6050.073529 \n",
+ "0 -0.192773 5725.785543 \n",
+ "1 -0.032678 5725.785543 \n",
+ "2 -0.166576 5725.785543 \n",
+ "3 -0.221944 5725.785543 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.077062 5585.176699 \n",
- "66 -0.163999 5585.176699 \n",
- "67 -0.028624 5535.318508 \n",
- "68 -0.057755 5535.318508 \n",
- "69 -0.043508 5535.318508 \n",
+ "65 -0.037183 6276.453840 \n",
+ "66 -0.061747 6276.453840 \n",
+ "67 NaN NaN \n",
+ "68 -0.040223 6276.453840 \n",
+ "69 NaN NaN \n",
"\n",
" Linear_test_R_2_after_ablation_10 XGB_Regressor_test_MSE_before_ablation \\\n",
- "0 -0.005489 3565.479582 \n",
- "1 -0.005489 3565.479582 \n",
- "2 -0.005489 3565.479582 \n",
- "3 -0.005489 3565.479582 \n",
- "4 -0.013764 3931.667854 \n",
+ "0 -0.007504 3494.999877 \n",
+ "1 -0.007504 3494.999877 \n",
+ "2 -0.007504 3494.999877 \n",
+ "3 -0.007504 3494.999877 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.002620 3725.748845 \n",
- "66 -0.002620 3725.748845 \n",
- "67 -0.008221 3761.115159 \n",
- "68 -0.008221 3761.115159 \n",
- "69 -0.008221 3761.115159 \n",
+ "65 -0.001477 4245.435413 \n",
+ "66 -0.001477 4245.435413 \n",
+ "67 NaN NaN \n",
+ "68 -0.001477 4245.435413 \n",
+ "69 NaN NaN \n",
"\n",
" XGB_Regressor_test_R_2_before_ablation \\\n",
- "0 0.375784 \n",
- "1 0.375784 \n",
- "2 0.375784 \n",
- "3 0.375784 \n",
- "4 0.341201 \n",
+ "0 0.385023 \n",
+ "1 0.385023 \n",
+ "2 0.385023 \n",
+ "3 0.385023 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.331174 \n",
- "66 0.331174 \n",
- "67 0.314938 \n",
- "68 0.314938 \n",
- "69 0.314938 \n",
+ "65 0.322594 \n",
+ "66 0.322594 \n",
+ "67 NaN \n",
+ "68 0.322594 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_1 \\\n",
- "0 4362.897831 \n",
- "1 4417.125378 \n",
- "2 4491.207741 \n",
- "3 4237.764376 \n",
- "4 4787.549007 \n",
+ "0 4013.099838 \n",
+ "1 4069.124107 \n",
+ "2 4139.604458 \n",
+ "3 4033.682012 \n",
+ "4 NaN \n",
".. ... \n",
- "65 4237.968847 \n",
- "66 4433.523117 \n",
- "67 4551.081588 \n",
- "68 4484.427719 \n",
- "69 4499.283634 \n",
+ "65 4744.258516 \n",
+ "66 4651.418299 \n",
+ "67 NaN \n",
+ "68 4453.127851 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_1 \\\n",
- "0 0.236179 \n",
- "1 0.226685 \n",
- "2 0.213715 \n",
- "3 0.258086 \n",
- "4 0.197788 \n",
+ "0 0.293859 \n",
+ "1 0.284001 \n",
+ "2 0.271599 \n",
+ "3 0.290237 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.239223 \n",
- "66 0.204119 \n",
- "67 0.171051 \n",
- "68 0.183191 \n",
- "69 0.180486 \n",
+ "65 0.243001 \n",
+ "66 0.257815 \n",
+ "67 NaN \n",
+ "68 0.289455 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_2 \\\n",
- "0 5082.947380 \n",
- "1 5059.030994 \n",
- "2 5325.002424 \n",
- "3 5120.520406 \n",
- "4 5654.969990 \n",
+ "0 5025.053741 \n",
+ "1 4989.273260 \n",
+ "2 4808.018366 \n",
+ "3 5034.332553 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5811.342427 \n",
- "66 5404.224345 \n",
- "67 5212.816093 \n",
- "68 5230.083512 \n",
- "69 4657.567836 \n",
+ "65 5134.835355 \n",
+ "66 5434.706040 \n",
+ "67 NaN \n",
+ "68 5212.469751 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_2 \\\n",
- "0 0.110118 \n",
- "1 0.114305 \n",
- "2 0.067741 \n",
- "3 0.103540 \n",
- "4 0.052441 \n",
+ "0 0.115796 \n",
+ "1 0.122092 \n",
+ "2 0.153986 \n",
+ "3 0.114164 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.043220 \n",
- "66 0.029864 \n",
- "67 0.050520 \n",
- "68 0.047375 \n",
- "69 0.151655 \n",
+ "65 0.180681 \n",
+ "66 0.132833 \n",
+ "67 NaN \n",
+ "68 0.168293 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_3 \\\n",
- "0 5443.059555 \n",
- "1 5123.918062 \n",
- "2 5404.375561 \n",
- "3 5318.162829 \n",
- "4 5475.757988 \n",
+ "0 5501.079765 \n",
+ "1 5539.634971 \n",
+ "2 5459.784944 \n",
+ "3 5587.280407 \n",
+ "4 NaN \n",
".. ... \n",
- "65 7035.886520 \n",
- "66 6252.311144 \n",
- "67 5727.578800 \n",
- "68 6147.504065 \n",
- "69 5698.794307 \n",
+ "65 5989.696026 \n",
+ "66 5996.028512 \n",
+ "67 NaN \n",
+ "68 6288.165970 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_3 \\\n",
- "0 0.047073 \n",
- "1 0.102945 \n",
- "2 0.053845 \n",
- "3 0.068939 \n",
- "4 0.082470 \n",
+ "0 0.032035 \n",
+ "1 0.025251 \n",
+ "2 0.039302 \n",
+ "3 0.016868 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.263043 \n",
- "66 -0.122380 \n",
- "67 -0.043240 \n",
- "68 -0.119727 \n",
- "69 -0.037997 \n",
+ "65 0.044278 \n",
+ "66 0.043268 \n",
+ "67 NaN \n",
+ "68 -0.003346 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_4 \\\n",
- "0 5747.170461 \n",
- "1 5524.767115 \n",
- "2 6105.030874 \n",
- "3 5673.859855 \n",
- "4 5690.431182 \n",
+ "0 5797.321121 \n",
+ "1 5753.544647 \n",
+ "2 5813.890743 \n",
+ "3 5743.479849 \n",
+ "4 NaN \n",
".. ... \n",
- "65 6466.436133 \n",
- "66 6135.927928 \n",
- "67 6311.016611 \n",
- "68 6596.737184 \n",
- "69 6048.504854 \n",
+ "65 6600.850248 \n",
+ "66 6553.462829 \n",
+ "67 NaN \n",
+ "68 6851.244552 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_4 \\\n",
- "0 -0.006169 \n",
- "1 0.032768 \n",
- "2 -0.068820 \n",
- "3 0.006666 \n",
- "4 0.046499 \n",
+ "0 -0.020091 \n",
+ "1 -0.012388 \n",
+ "2 -0.023007 \n",
+ "3 -0.010617 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.160819 \n",
- "66 -0.101488 \n",
- "67 -0.149510 \n",
- "68 -0.201552 \n",
- "69 -0.101695 \n",
+ "65 -0.053238 \n",
+ "66 -0.045677 \n",
+ "67 NaN \n",
+ "68 -0.093191 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_5 \\\n",
- "0 5782.250032 \n",
- "1 5776.289705 \n",
- "2 6161.928219 \n",
- "3 6080.111206 \n",
- "4 5921.843788 \n",
+ "0 5843.247374 \n",
+ "1 5721.953538 \n",
+ "2 5752.146408 \n",
+ "3 5912.545974 \n",
+ "4 NaN \n",
".. ... \n",
- "65 6318.690304 \n",
- "66 6393.470622 \n",
- "67 6614.314282 \n",
- "68 6460.519172 \n",
- "69 6602.231271 \n",
+ "65 6439.163654 \n",
+ "66 6346.476672 \n",
+ "67 NaN \n",
+ "68 6812.276313 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_5 \\\n",
- "0 -0.012310 \n",
- "1 -0.011267 \n",
- "2 -0.078781 \n",
- "3 -0.064457 \n",
- "4 0.007723 \n",
+ "0 -0.028172 \n",
+ "1 -0.006829 \n",
+ "2 -0.012142 \n",
+ "3 -0.040366 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.134296 \n",
- "66 -0.147720 \n",
- "67 -0.204753 \n",
- "68 -0.176740 \n",
- "69 -0.202552 \n",
+ "65 -0.027439 \n",
+ "66 -0.012650 \n",
+ "67 NaN \n",
+ "68 -0.086974 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_6 \\\n",
- "0 5830.867264 \n",
- "1 6083.961808 \n",
- "2 6084.476971 \n",
- "3 6056.849952 \n",
- "4 5940.795730 \n",
+ "0 5892.623117 \n",
+ "1 6011.466936 \n",
+ "2 5743.704769 \n",
+ "3 5896.718386 \n",
+ "4 NaN \n",
".. ... \n",
- "65 6248.073414 \n",
- "66 6529.782934 \n",
- "67 6483.378328 \n",
- "68 6583.652258 \n",
- "69 6440.659192 \n",
+ "65 6425.883090 \n",
+ "66 6452.011697 \n",
+ "67 NaN \n",
+ "68 6928.881119 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_6 \\\n",
- "0 -0.020822 \n",
- "1 -0.065131 \n",
- "2 -0.065222 \n",
- "3 -0.060385 \n",
- "4 0.004547 \n",
+ "0 -0.036860 \n",
+ "1 -0.057772 \n",
+ "2 -0.010657 \n",
+ "3 -0.037581 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.121619 \n",
- "66 -0.172190 \n",
- "67 -0.180904 \n",
- "68 -0.199168 \n",
- "69 -0.173123 \n",
+ "65 -0.025320 \n",
+ "66 -0.029489 \n",
+ "67 NaN \n",
+ "68 -0.105579 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_7 \\\n",
- "0 5832.799073 \n",
- "1 5755.751419 \n",
- "2 6072.037858 \n",
- "3 6114.234944 \n",
- "4 6009.317532 \n",
+ "0 5822.535066 \n",
+ "1 5901.583727 \n",
+ "2 5795.713241 \n",
+ "3 6061.503398 \n",
+ "4 NaN \n",
".. ... \n",
- "65 6390.760993 \n",
- "66 6440.441698 \n",
- "67 5960.523436 \n",
- "68 6573.851529 \n",
- "69 6118.444678 \n",
+ "65 6511.903490 \n",
+ "66 6466.410333 \n",
+ "67 NaN \n",
+ "68 6522.271203 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_7 \\\n",
- "0 -0.021160 \n",
- "1 -0.007671 \n",
- "2 -0.063044 \n",
- "3 -0.070431 \n",
- "4 -0.006934 \n",
+ "0 -0.024528 \n",
+ "1 -0.038437 \n",
+ "2 -0.019808 \n",
+ "3 -0.066576 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.147234 \n",
- "66 -0.156152 \n",
- "67 -0.085670 \n",
- "68 -0.197383 \n",
- "69 -0.114434 \n",
+ "65 -0.039046 \n",
+ "66 -0.031787 \n",
+ "67 NaN \n",
+ "68 -0.040700 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_8 \\\n",
- "0 5886.180420 \n",
- "1 5791.839463 \n",
- "2 6164.297845 \n",
- "3 6259.056809 \n",
- "4 6309.394957 \n",
+ "0 5913.358559 \n",
+ "1 5897.320816 \n",
+ "2 5876.811017 \n",
+ "3 6057.537598 \n",
+ "4 NaN \n",
".. ... \n",
- "65 6417.178461 \n",
- "66 6627.164328 \n",
- "67 6015.960917 \n",
- "68 6295.371009 \n",
- "69 6293.345882 \n",
+ "65 6526.163669 \n",
+ "66 6456.925559 \n",
+ "67 NaN \n",
+ "68 6489.344892 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_8 \\\n",
- "0 -0.030505 \n",
- "1 -0.013989 \n",
- "2 -0.079196 \n",
- "3 -0.095786 \n",
- "4 -0.057216 \n",
+ "0 -0.040509 \n",
+ "1 -0.037687 \n",
+ "2 -0.034078 \n",
+ "3 -0.065878 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.151976 \n",
- "66 -0.189672 \n",
- "67 -0.095767 \n",
- "68 -0.146660 \n",
- "69 -0.146291 \n",
+ "65 -0.041321 \n",
+ "66 -0.030273 \n",
+ "67 NaN \n",
+ "68 -0.035446 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_9 \\\n",
- "0 5843.408829 \n",
- "1 5875.728030 \n",
- "2 6121.536055 \n",
- "3 6129.607419 \n",
- "4 6453.157959 \n",
+ "0 5945.208529 \n",
+ "1 5938.553679 \n",
+ "2 5907.525792 \n",
+ "3 5972.670797 \n",
+ "4 NaN \n",
".. ... \n",
- "65 6340.479231 \n",
- "66 6234.587550 \n",
- "67 6115.491296 \n",
- "68 6204.552633 \n",
- "69 6083.916220 \n",
+ "65 6501.302701 \n",
+ "66 6384.095136 \n",
+ "67 NaN \n",
+ "68 6399.173120 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_9 \\\n",
- "0 -0.023017 \n",
- "1 -0.028676 \n",
- "2 -0.071710 \n",
- "3 -0.073123 \n",
- "4 -0.081305 \n",
+ "0 -0.046113 \n",
+ "1 -0.044942 \n",
+ "2 -0.039483 \n",
+ "3 -0.050945 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.138207 \n",
- "66 -0.119198 \n",
- "67 -0.113896 \n",
- "68 -0.130118 \n",
- "69 -0.108145 \n",
+ "65 -0.037354 \n",
+ "66 -0.018652 \n",
+ "67 NaN \n",
+ "68 -0.021058 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_MSE_after_ablation_10 \\\n",
- "0 6007.922958 \n",
- "1 6007.922958 \n",
- "2 6007.922958 \n",
- "3 6007.922958 \n",
- "4 6395.094041 \n",
+ "0 5919.422152 \n",
+ "1 5919.422152 \n",
+ "2 5919.422152 \n",
+ "3 5919.422152 \n",
+ "4 NaN \n",
".. ... \n",
- "65 6392.430662 \n",
- "66 6392.430662 \n",
- "67 6154.257530 \n",
- "68 6154.257530 \n",
- "69 6154.257530 \n",
+ "65 6267.370049 \n",
+ "66 6267.370049 \n",
+ "67 NaN \n",
+ "68 6267.370049 \n",
+ "69 NaN \n",
"\n",
" XGB_Regressor_test_R_2_after_ablation_10 \\\n",
- "0 -0.051819 \n",
- "1 -0.051819 \n",
- "2 -0.051819 \n",
- "3 -0.051819 \n",
- "4 -0.071576 \n",
+ "0 -0.041576 \n",
+ "1 -0.041576 \n",
+ "2 -0.041576 \n",
+ "3 -0.041576 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.147533 \n",
- "66 -0.147533 \n",
- "67 -0.120957 \n",
- "68 -0.120957 \n",
- "69 -0.120957 \n",
+ "65 -0.000028 \n",
+ "66 -0.000028 \n",
+ "67 NaN \n",
+ "68 -0.000028 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_before_ablation \\\n",
- "0 3068.863830 \n",
- "1 3068.863830 \n",
- "2 3068.863830 \n",
- "3 3068.863830 \n",
- "4 3392.891623 \n",
+ "0 2466.857536 \n",
+ "1 2466.857536 \n",
+ "2 2466.857536 \n",
+ "3 2466.857536 \n",
+ "4 NaN \n",
".. ... \n",
- "65 3043.279335 \n",
- "66 3043.279335 \n",
- "67 3139.516608 \n",
- "68 3139.516608 \n",
- "69 3139.516608 \n",
+ "65 3251.341447 \n",
+ "66 3251.341447 \n",
+ "67 NaN \n",
+ "68 3251.341447 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_before_ablation \\\n",
- "0 0.462728 \n",
- "1 0.462728 \n",
- "2 0.462728 \n",
- "3 0.462728 \n",
- "4 0.431480 \n",
+ "0 0.565934 \n",
+ "1 0.565934 \n",
+ "2 0.565934 \n",
+ "3 0.565934 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.453687 \n",
- "66 0.453687 \n",
- "67 0.428158 \n",
- "68 0.428158 \n",
- "69 0.428158 \n",
+ "65 0.481213 \n",
+ "66 0.481213 \n",
+ "67 NaN \n",
+ "68 0.481213 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_1 \\\n",
- "0 3818.286646 \n",
- "1 3824.162442 \n",
- "2 3827.072282 \n",
- "3 3732.654148 \n",
- "4 4191.710491 \n",
+ "0 3486.670871 \n",
+ "1 3512.809915 \n",
+ "2 3387.295959 \n",
+ "3 3413.979947 \n",
+ "4 NaN \n",
".. ... \n",
- "65 3747.546011 \n",
- "66 3916.359829 \n",
- "67 3949.965025 \n",
- "68 3882.799563 \n",
- "69 3761.727998 \n",
+ "65 4245.552249 \n",
+ "66 4151.615634 \n",
+ "67 NaN \n",
+ "68 4185.950870 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_1 \\\n",
- "0 0.331525 \n",
- "1 0.330496 \n",
- "2 0.329987 \n",
- "3 0.346517 \n",
- "4 0.297628 \n",
+ "0 0.386489 \n",
+ "1 0.381889 \n",
+ "2 0.403975 \n",
+ "3 0.399279 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.327261 \n",
- "66 0.296957 \n",
- "67 0.280540 \n",
- "68 0.292774 \n",
- "69 0.314826 \n",
+ "65 0.322576 \n",
+ "66 0.337564 \n",
+ "67 NaN \n",
+ "68 0.332086 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_2 \\\n",
- "0 4914.443118 \n",
- "1 4707.799112 \n",
- "2 4716.561876 \n",
- "3 4726.437509 \n",
- "4 5399.696626 \n",
+ "0 4501.848106 \n",
+ "1 4466.543184 \n",
+ "2 4267.977699 \n",
+ "3 4484.335122 \n",
+ "4 NaN \n",
".. ... \n",
- "65 4388.732777 \n",
- "66 4555.396175 \n",
- "67 4609.805293 \n",
- "68 4562.861560 \n",
- "69 4420.406856 \n",
+ "65 4889.454447 \n",
+ "66 5150.085657 \n",
+ "67 NaN \n",
+ "68 5088.527932 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_2 \\\n",
- "0 0.139619 \n",
- "1 0.175796 \n",
- "2 0.174262 \n",
- "3 0.172533 \n",
- "4 0.095215 \n",
+ "0 0.207859 \n",
+ "1 0.214071 \n",
+ "2 0.249011 \n",
+ "3 0.210941 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.212159 \n",
- "66 0.182241 \n",
- "67 0.160355 \n",
- "68 0.168905 \n",
- "69 0.194852 \n",
+ "65 0.219834 \n",
+ "66 0.178247 \n",
+ "67 NaN \n",
+ "68 0.188069 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_3 \\\n",
- "0 5558.586043 \n",
- "1 5259.040670 \n",
- "2 5153.033770 \n",
- "3 5427.336730 \n",
- "4 5851.776337 \n",
+ "0 5291.148962 \n",
+ "1 5265.613075 \n",
+ "2 4967.246258 \n",
+ "3 5200.283806 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5042.162467 \n",
- "66 5116.362836 \n",
- "67 5102.378012 \n",
- "68 5160.712830 \n",
- "69 5086.133038 \n",
+ "65 5673.355569 \n",
+ "66 5841.931213 \n",
+ "67 NaN \n",
+ "68 5921.367059 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_3 \\\n",
- "0 0.026847 \n",
- "1 0.079289 \n",
- "2 0.097848 \n",
- "3 0.049825 \n",
- "4 0.019464 \n",
+ "0 0.068975 \n",
+ "1 0.073468 \n",
+ "2 0.125968 \n",
+ "3 0.084963 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.094859 \n",
- "66 0.081539 \n",
- "67 0.070636 \n",
- "68 0.060011 \n",
- "69 0.073595 \n",
+ "65 0.094754 \n",
+ "66 0.067856 \n",
+ "67 NaN \n",
+ "68 0.055181 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_4 \\\n",
- "0 5832.603810 \n",
- "1 5575.386841 \n",
- "2 5434.084925 \n",
- "3 5680.278030 \n",
- "4 6018.755220 \n",
+ "0 5664.603936 \n",
+ "1 5697.985065 \n",
+ "2 5421.823682 \n",
+ "3 5660.252160 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5459.350264 \n",
- "66 5520.772874 \n",
- "67 5422.380406 \n",
- "68 5366.841728 \n",
- "69 5394.059982 \n",
+ "65 6124.177802 \n",
+ "66 6257.791966 \n",
+ "67 NaN \n",
+ "68 6385.221264 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_4 \\\n",
- "0 -0.021126 \n",
- "1 0.023906 \n",
- "2 0.048644 \n",
- "3 0.005542 \n",
- "4 -0.008516 \n",
+ "0 0.003262 \n",
+ "1 -0.002612 \n",
+ "2 0.045981 \n",
+ "3 0.004028 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.019968 \n",
- "66 0.008942 \n",
- "67 0.012350 \n",
- "68 0.022466 \n",
- "69 0.017508 \n",
+ "65 0.022820 \n",
+ "66 0.001501 \n",
+ "67 NaN \n",
+ "68 -0.018832 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_5 \\\n",
- "0 5784.351708 \n",
- "1 5723.134442 \n",
- "2 5554.591693 \n",
- "3 5833.784358 \n",
- "4 6071.573392 \n",
+ "0 5755.469084 \n",
+ "1 5747.874691 \n",
+ "2 5654.847385 \n",
+ "3 5774.580841 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5555.680287 \n",
- "66 5789.702012 \n",
- "67 5611.746572 \n",
- "68 5591.524535 \n",
- "69 5571.039679 \n",
+ "65 6225.744929 \n",
+ "66 6220.642475 \n",
+ "67 NaN \n",
+ "68 6420.552407 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_5 \\\n",
- "0 -0.012678 \n",
- "1 -0.001961 \n",
- "2 0.027546 \n",
- "3 -0.021332 \n",
- "4 -0.017366 \n",
+ "0 -0.012727 \n",
+ "1 -0.011390 \n",
+ "2 0.004979 \n",
+ "3 -0.016090 \n",
+ "4 NaN \n",
".. ... \n",
- "65 0.002675 \n",
- "66 -0.039335 \n",
- "67 -0.022142 \n",
- "68 -0.018459 \n",
- "69 -0.014728 \n",
+ "65 0.006614 \n",
+ "66 0.007428 \n",
+ "67 NaN \n",
+ "68 -0.024470 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_6 \\\n",
- "0 5793.649629 \n",
- "1 5771.443274 \n",
- "2 5635.787161 \n",
- "3 5714.152885 \n",
- "4 6010.857279 \n",
+ "0 5712.231598 \n",
+ "1 5760.576056 \n",
+ "2 5686.740295 \n",
+ "3 5706.121381 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5702.488350 \n",
- "66 5781.533396 \n",
- "67 5650.413900 \n",
- "68 5634.800732 \n",
- "69 5549.016093 \n",
+ "65 6230.183531 \n",
+ "66 6374.114987 \n",
+ "67 NaN \n",
+ "68 6519.528273 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_6 \\\n",
- "0 -0.014306 \n",
- "1 -0.010418 \n",
- "2 0.013331 \n",
- "3 -0.000388 \n",
- "4 -0.007192 \n",
+ "0 -0.005119 \n",
+ "1 -0.013625 \n",
+ "2 -0.000633 \n",
+ "3 -0.004044 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.023679 \n",
- "66 -0.037869 \n",
- "67 -0.029185 \n",
- "68 -0.026341 \n",
- "69 -0.010716 \n",
+ "65 0.005906 \n",
+ "66 -0.017060 \n",
+ "67 NaN \n",
+ "68 -0.040262 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_7 \\\n",
- "0 5799.895490 \n",
- "1 5830.381002 \n",
- "2 5763.684469 \n",
- "3 5797.828571 \n",
- "4 6042.684405 \n",
+ "0 5715.404233 \n",
+ "1 5691.234177 \n",
+ "2 5670.736069 \n",
+ "3 5733.989985 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5680.464377 \n",
- "66 5764.376455 \n",
- "67 5624.395688 \n",
- "68 5614.899058 \n",
- "69 5631.833473 \n",
+ "65 6331.818864 \n",
+ "66 6474.285866 \n",
+ "67 NaN \n",
+ "68 6451.424694 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_7 \\\n",
- "0 -0.015399 \n",
- "1 -0.020737 \n",
- "2 -0.009060 \n",
- "3 -0.015038 \n",
- "4 -0.012525 \n",
+ "0 -0.005677 \n",
+ "1 -0.001424 \n",
+ "2 0.002183 \n",
+ "3 -0.008947 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.019725 \n",
- "66 -0.034789 \n",
- "67 -0.024446 \n",
- "68 -0.022716 \n",
- "69 -0.025801 \n",
+ "65 -0.010311 \n",
+ "66 -0.033043 \n",
+ "67 NaN \n",
+ "68 -0.029396 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_8 \\\n",
- "0 5799.531819 \n",
- "1 5789.080541 \n",
- "2 5807.287765 \n",
- "3 5811.450208 \n",
- "4 6090.457960 \n",
+ "0 5698.990643 \n",
+ "1 5656.583805 \n",
+ "2 5696.299307 \n",
+ "3 5727.995769 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5695.898765 \n",
- "66 5799.731329 \n",
- "67 5597.750571 \n",
- "68 5613.153894 \n",
- "69 5591.152466 \n",
+ "65 6421.566444 \n",
+ "66 6449.857168 \n",
+ "67 NaN \n",
+ "68 6391.825749 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_8 \\\n",
- "0 -0.015336 \n",
- "1 -0.013506 \n",
- "2 -0.016694 \n",
- "3 -0.017422 \n",
- "4 -0.020530 \n",
+ "0 -0.002789 \n",
+ "1 0.004673 \n",
+ "2 -0.002315 \n",
+ "3 -0.007893 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.022496 \n",
- "66 -0.041135 \n",
- "67 -0.019593 \n",
- "68 -0.022399 \n",
- "69 -0.018391 \n",
+ "65 -0.024631 \n",
+ "66 -0.029146 \n",
+ "67 NaN \n",
+ "68 -0.019886 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_9 \\\n",
- "0 5783.277353 \n",
- "1 5778.531386 \n",
- "2 5761.554160 \n",
- "3 5807.028565 \n",
- "4 6081.173795 \n",
+ "0 5717.216380 \n",
+ "1 5670.693792 \n",
+ "2 5690.972357 \n",
+ "3 5704.121340 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5664.517560 \n",
- "66 5737.201421 \n",
- "67 5626.025263 \n",
- "68 5620.507263 \n",
- "69 5590.145323 \n",
+ "65 6365.125200 \n",
+ "66 6360.266687 \n",
+ "67 NaN \n",
+ "68 6293.769573 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_9 \\\n",
- "0 -0.012490 \n",
- "1 -0.011659 \n",
- "2 -0.008687 \n",
- "3 -0.016648 \n",
- "4 -0.018975 \n",
+ "0 -0.005996 \n",
+ "1 0.002190 \n",
+ "2 -0.001378 \n",
+ "3 -0.003692 \n",
+ "4 NaN \n",
".. ... \n",
- "65 -0.016863 \n",
- "66 -0.029910 \n",
- "67 -0.024743 \n",
- "68 -0.023738 \n",
- "69 -0.018208 \n",
+ "65 -0.015626 \n",
+ "66 -0.014850 \n",
+ "67 NaN \n",
+ "68 -0.004240 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_MSE_after_ablation_10 \\\n",
- "0 5775.798475 \n",
- "1 5775.798475 \n",
- "2 5775.798475 \n",
- "3 5775.798475 \n",
- "4 6099.151078 \n",
+ "0 5691.215026 \n",
+ "1 5691.215026 \n",
+ "2 5691.215026 \n",
+ "3 5691.215026 \n",
+ "4 NaN \n",
".. ... \n",
- "65 5655.363927 \n",
- "66 5655.363927 \n",
- "67 5636.734002 \n",
- "68 5636.734002 \n",
- "69 5636.734002 \n",
+ "65 6267.614305 \n",
+ "66 6267.614305 \n",
+ "67 NaN \n",
+ "68 6267.614305 \n",
+ "69 NaN \n",
"\n",
" RF_Plus_Regressor_test_R_2_after_ablation_10 test_data_ablation_time \\\n",
- "0 -0.011181 8.891757 \n",
- "1 -0.011181 8.881537 \n",
- "2 -0.011181 8.914796 \n",
- "3 -0.011181 8.867040 \n",
- "4 -0.021987 8.382616 \n",
+ "0 -0.001421 8.682843 \n",
+ "1 -0.001421 8.740817 \n",
+ "2 -0.001421 8.665586 \n",
+ "3 -0.001421 8.887087 \n",
+ "4 NaN NaN \n",
".. ... ... \n",
- "65 -0.015219 7.412112 \n",
- "66 -0.015219 7.402059 \n",
- "67 -0.026693 7.036491 \n",
- "68 -0.026693 7.033576 \n",
- "69 -0.026693 6.885340 \n",
+ "65 -0.000067 9.768127 \n",
+ "66 -0.000067 9.973668 \n",
+ "67 NaN NaN \n",
+ "68 -0.000067 9.742957 \n",
+ "69 NaN NaN \n",
"\n",
" split_seed rf_model \n",
- "0 4 NaN \n",
- "1 4 NaN \n",
- "2 4 NaN \n",
- "3 4 NaN \n",
- "4 4 RandomForestRegressor(max_features=0.33, min_s... \n",
+ "0 9 NaN \n",
+ "1 9 NaN \n",
+ "2 9 NaN \n",
+ "3 9 NaN \n",
+ "4 9 RandomForestRegressor(max_features=0.33, min_s... \n",
".. ... ... \n",
- "65 6 NaN \n",
- "66 6 NaN \n",
- "67 6 RandomForestRegressor(max_features=0.33, min_s... \n",
- "68 6 RandomForestRegressor(max_features=0.33, min_s... \n",
- "69 6 RandomForestRegressor(max_features=0.33, min_s... \n",
+ "65 10 NaN \n",
+ "66 10 NaN \n",
+ "67 10 RandomForestRegressor(max_features=0.33, min_s... \n",
+ "68 10 RandomForestRegressor(max_features=0.33, min_s... \n",
+ "69 10 RandomForestRegressor(max_features=0.33, min_s... \n",
"\n",
- "[70 rows x 302 columns]"
+ "[70 rows x 580 columns]"
]
},
"execution_count": 4,
@@ -6140,13 +12245,13 @@
"output_type": "stream",
"text": [
" fi fi_time\n",
- "0 Kernel_SHAP_RF_plus 277.088223\n",
- "1 LFI_with_raw_OOB_RF 6.107385\n",
- "2 LFI_with_raw_RF 6.842227\n",
- "3 LFI_with_raw_RF_plus 1.639075\n",
- "4 LIME_RF_plus 612.684298\n",
- "5 MDI_RF 2.537897\n",
- "6 TreeSHAP_RF 0.334840\n"
+ "0 Kernel_SHAP_RF_plus 112.383354\n",
+ "1 LFI_with_raw_OOB_RF 7.247704\n",
+ "2 LFI_with_raw_RF 8.086560\n",
+ "3 LFI_with_raw_RF_plus 1.960254\n",
+ "4 LIME_RF_plus 246.317087\n",
+ "5 MDI_RF 3.232473\n",
+ "6 TreeSHAP_RF 0.283622\n"
]
}
],
@@ -6160,48 +12265,22 @@
"cell_type": "code",
"execution_count": 6,
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " fi train_data_ablation_time\n",
- "0 Kernel_SHAP_RF_plus 10.402297\n",
- "1 LFI_with_raw_OOB_RF 10.521922\n",
- "2 LFI_with_raw_RF 10.535834\n",
- "3 LFI_with_raw_RF_plus 10.385392\n",
- "4 LIME_RF_plus 10.394773\n",
- "5 MDI_RF 10.534780\n",
- "6 TreeSHAP_RF 10.418015\n"
- ]
- }
- ],
- "source": [
- "# Print the ablation time\n",
- "averages = combined_df.groupby('fi')['train_data_ablation_time'].mean().reset_index()\n",
- "print(averages)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
"outputs": [],
"source": [
"#################### Change the following according to the dataset ####################\n",
"task = \"regression\" #\"regression\" \"classification\"\n",
"########################################################################################\n",
- "methods_rf = [\"LFI_with_raw_RF\", \"LFI_with_raw_CV_RF\", \"LFI_with_raw_OOB_RF\", \"MDI_RF\", \"TreeSHAP_RF\"]\n",
- "methods_rf_plus = [\"Kernel_SHAP_RF_plus\",\"LFI_with_raw_RF_plus\", \"LIME_RF_plus\"]\n",
- "methods_all = methods_rf + methods_rf_plus\n",
+ "methods_all = combined_df['fi'].drop_duplicates().tolist()\n",
"n_testsize = combined_df[['train_size', 'test_size']].drop_duplicates()\n",
"num_features = combined_df['num_features'].drop_duplicates()[0]\n",
- "metrics = {\"regression\": [\"MSE\", \"R_2\"], \"classification\": [\"AUROC\",\"AUPRC\", \"F1\"]}"
+ "metrics = {\"regression\": [\"MSE\", \"R_2\"], \"classification\": [\"AUROC\",\"AUPRC\", \"F1\"]}\n",
+ "ablation_models = {\"regression\": [\"RF_Regressor\", \"Linear\", \"XGB_Regressor\", \"RF_Plus_Regressor\"], \n",
+ " \"classification\": [\"RF_Classifier\",\"LogisticCV\", \"SVM\", \"XGBoost_Classifier\", \"RF_Plus_Classifier\"]}"
]
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 7,
"metadata": {},
"outputs": [
{
@@ -6209,13 +12288,11 @@
"output_type": "stream",
"text": [
"Model: RF\n",
- "MSE before ablation: 3160.159277609703\n",
- "R2 before ablation: 0.4474091923958154\n",
- "\n",
+ "MSE: 3160.159277609703\n",
+ "R2: 0.4474091923958154\n",
"Model: RF_plus\n",
- "MSE before ablation: 3058.492966541393\n",
- "R2 before ablation: 0.4653868933792268\n",
- "\n"
+ "MSE: 3058.4929665413924\n",
+ "R2: 0.4653868933792266\n"
]
}
],
@@ -6224,26 +12301,15 @@
" grouped = combined_df.groupby(\"model\")\n",
" for model, group_df in grouped:\n",
" print(\"Model:\", model)\n",
- " print(\"AUROC before ablation:\", group_df[\"test_all_auc\"].mean())\n",
- " print(\"AUPRC before ablation:\", group_df[\"test_all_auprc\"].mean())\n",
- " print(\"F1 before ablation:\", group_df[\"test_all_f1\"].mean())\n",
- " print()\n",
+ " print(\"AUROC:\", group_df[\"test_all_auc\"].mean())\n",
+ " print(\"AUPRC:\", group_df[\"test_all_auprc\"].mean())\n",
+ " print(\"F1:\", group_df[\"test_all_f1\"].mean())\n",
"elif task == \"regression\":\n",
" grouped = combined_df.groupby(\"model\")\n",
" for model, group_df in grouped:\n",
" print(\"Model:\", model)\n",
- " print(\"MSE before ablation:\", group_df[\"test_all_mse\"].mean())\n",
- " print(\"R2 before ablation:\", group_df[\"test_all_r2\"].mean())\n",
- " print()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [],
- "source": [
- "ablation_models = {\"regression\": [\"RF_Regressor\", \"Linear\", \"XGB_Regressor\", \"RF_Plus_Regressor\"], \"classification\": [\"RF_Classifier\",\"Logistic\", \"SVM\", \"XGBoost_Classifier\", \"RF_Plus_Classifier\"]}"
+ " print(\"MSE:\", group_df[\"test_all_mse\"].mean())\n",
+ " print(\"R2:\", group_df[\"test_all_r2\"].mean())"
]
},
{
@@ -6255,84 +12321,123 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": "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",
- "text/plain": [
- "