Feature Importance using decision tree

Hi Everybody,

I have a question is it possible to extract feature importance in Knime using decision tree learner and predictor?

Using sklearn I usual use the following code for it:

from sklearn.tree import DecisionTreeClassifier
dt = DecisionTreeClassifier()
dt.fit(X_train, y_train)
dt.score(X_test, y_test)

dt.feature_importances_

For sure I could use the python node, but I try to transfer my normal tasks to KNIME without using python.
Does somebody have an idea?

Hello @sschacht,

see these two topics:


Br,
Ivan

Hi @sschacht
Maybe the Information Gain Calculator helps you to give some insights about the feature importance.
gr. Hans

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