Understand Tree Decision

[ipazin]

Hello @AnaBerta,

and welcome to KNIME and it’s Community!

@AnaBerta

it´s possible to know what fields have more weight in the decision?

Sure there is. In case of Decision Tree algorithm (which has tree structure as output) the top-level features are the more important that the others.

Check this topic with further topics linked for more about it:

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?

Br,
Ivan