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I am using (and loving) Orange 3 for some projects at my school and have a question:

When using Python and e.g. doing a RandomForest Classification, I can easily access the feature importances by feature_importances_

In Orange 3 there seems to be no feature to access that in the visual programming interface (would be a great add-on), so I tried to write my own python script in orange...

I linked the RandomForest Classifier to the Python script widget's in_classifier and have the following code:

print(in_classifier)
importances = in_classifier.feature_importances_

The result is however:

Random Forest Classification {'random_state': 0, 'n_estimators': 500, 'n_jobs': 1, 'min_samples_leaf': 1, 'max_leaf_nodes': None, 'max_features': 'auto', 'bootstrap': True, 'verbose': 0, 'max_depth': None, 'oob_score': False, 'min_samples_split': 2, 'class_weight': None, 'min_weight_fraction_leaf': 0.0, 'criterion': 'gini'}
    Traceback (most recent call last):
      File "", line 1, in 
      File "", line 2, in 
    AttributeError: 'RandomForestClassifier' object has no attribute 'feature_importances_'

=> I don't understand whey the RandomForestClassifier Object doesn't provide this array?

Anyone any idea?

many thanks!!

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You can connect Random Forest widget into Rank widget, which I guess is meant for subset feature selection. See Orange screenshot #19.

Model-based feature selection with Orange Rank widget

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