CODEWITHSUNDEEP
pythonscikit-learn
Aleksandar Beat
Aleksandar Beat

Reputation: 201

Decision Tree - most influential parameter Python

I have simple Decision Tree program in Python. Is there a way to find out (print) the most influential parameter (or more of them) from X that caused the result? For example: "the predicted result is "yes". The most influential parameters are [0] values in items of X"

from sklearn import tree


X=[[100,3],[130,3],[80,2],[90,2],[140,3]]
Y=["yes","no","yes","yes","no"]

clf = tree.DecisionTreeClassifier()

clf = clf.fit(X,Y)

List1=[124,3]

prediction = clf.predict([List1])

print(prediction)

Upvotes: 1

Views: 728

Answers (1)

Seljuk Gulcan
Seljuk Gulcan

Reputation: 1868

feature_importances_ attribute can be used.

The feature importances. The higher, the more important the feature. The importance of a feature is computed as the (normalized) total reduction of the criterion brought by that feature.

http://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html

print(clf.feature_importances_)
> [1. 0.]

Here second feature importance is zero, it means this feature is not included in the rule tree.

Upvotes: 1

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