Details
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New Feature
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Status: Closed
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Major
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Resolution: Fixed
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Description
From the Breiman resource that we use for random forest:
Gini importance
Every time a split of a node is made on variable m the gini impurity criterion for the two descendent nodes is less than the parent node. Adding up the gini decreases for each individual variable over all trees in the forest gives a fast variable importance that is often very consistent with the permutation importance measure.
We can add a similar measure in our DT code called as impurity_variable_importance.
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