diff --git a/CHANGELOG.md b/CHANGELOG.md
index 7cabe45..5b310bb 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,4 +1,8 @@
 # Changes
+# 2.2.0
+ - [BUG] fix the collinearity feature elimination
+ - [BUG] fix the feature importance if fasttreeshap not installed
+ - [REFACTORING] refactor the association module for removing redundancy and faster computation
 # 2.1.3
  - [BUG] fix the hardcoded threshold in collinearity elimination, closes #33
 # 2.1.2
diff --git a/src/arfs/feature_selection/mrmr.py b/src/arfs/feature_selection/mrmr.py
index 11b74d1..de4b087 100644
--- a/src/arfs/feature_selection/mrmr.py
+++ b/src/arfs/feature_selection/mrmr.py
@@ -110,7 +110,7 @@ def __init__(
         denominator_func=np.mean,
         only_same_domain=False,
         return_scores=False,
-        n_jobs=-1,
+        n_jobs=1,
         show_progress=True,
     ):
         self.n_features_to_select = n_features_to_select
diff --git a/src/arfs/feature_selection/unsupervised.py b/src/arfs/feature_selection/unsupervised.py
index 318842d..a5b85e4 100644
--- a/src/arfs/feature_selection/unsupervised.py
+++ b/src/arfs/feature_selection/unsupervised.py
@@ -27,7 +27,14 @@
 # ARFS
 from .base import BaseThresholdSelector
 from ..utils import create_dtype_dict
-from ..association import association_matrix, xy_to_matrix, plot_association_matrix
+from ..association import (
+    association_matrix,
+    xy_to_matrix,
+    plot_association_matrix,
+    weighted_theils_u,
+    weighted_corr,
+    correlation_ratio,
+)
 from ..preprocessing import OrdinalEncoderPandas
 
 
@@ -296,10 +303,10 @@ def __init__(
         self,
         threshold=0.80,
         method="association",
-        n_jobs=-1,
-        nom_nom_assoc="theil",
-        num_num_assoc="spearman",
-        nom_num_assoc="correlation_ratio",
+        n_jobs=1,
+        nom_nom_assoc=weighted_theils_u,
+        num_num_assoc=weighted_corr,
+        nom_num_assoc=correlation_ratio,
     ):
         self.threshold = threshold
         self.method = method
@@ -444,7 +451,7 @@ def _recursive_collinear_elimination(association_matrix, threshold):
 
     while True:
         most_collinear_feature, to_drop = _most_collinear(dum, threshold)
-        
+
         # Break if no more features to drop
         if not to_drop:
             break
@@ -453,4 +460,4 @@ def _recursive_collinear_elimination(association_matrix, threshold):
             most_collinear_features.append(most_collinear_feature)
             dum = dum.drop(columns=most_collinear_feature, index=most_collinear_feature)
 
-    return most_collinear_features
\ No newline at end of file
+    return most_collinear_features