In the context of decision trees, what is "information gain" used for?
- To assess the tree's overall accuracy
- To calculate the depth of the tree
- To determine the number of leaf nodes
- To measure the purity of a split
Information gain is used to measure the purity of a split in a decision tree. It helps decide which feature to split on by evaluating how much it reduces uncertainty or entropy.
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