Decision Trees: “Gini” vs. “Entropy” criteria
The scikit-learn documentation1 has an argument to control how the decision tree algorithm splits nodes: criterion : string, optional (default=”gini”) The function to measure the quality of a split. Supported criteria are “gini” for the Gini impurity and “entropy” for the information gain. It seems like something that could be important since this determines the …
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