Decision Tree visualize wrong path

[wim50594]

Description
If the path of a DecisionTree is to be visualized for a single instance and the feature value is exactly the split value, the right path is selected. However, with Sklearn, the decision goes left for less than or equal to. In the end, an incorrect classification is displayed due to the wrong path.

To Reproduce

import dtreeviz
import numpy as np
import sklearn.tree
from sklearn.tree import DecisionTreeClassifier

X = np.expand_dims(np.arange(10), axis=1)
y = np.asarray(5*[False] + 5*[True])

clf = DecisionTreeClassifier().fit(X, y)

sklearn.tree.plot_tree(clf, class_names=["False", "True"])

viz_model = dtreeviz.model(clf, X_train=X, y_train=y, class_names=["False", "True"], feature_names='x1')
viz_model.view()

x = np.asarray([4.5])
clf.predict([x])
# outputs array([False])

x = np.asarray([4.5])
viz_model.view(x=x)

Expected behavior
The left path should be chosen and thus the classification result "False" should also be displayed. In other words: If the split value is less than or equal to the split value, the left path should be selected.

Environment
Used scikit-learn version 1.2.2 (lates)

[tlapusan]

Thanks @wim50594, it helps that you created the steps to reproduce the issue. I will take a look soon, right now I'm in vacation.