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When splitting data into branches for a decision tree, what kind of feature is favored and chosen first? 1 point The feature that increases entropy
When splitting data into branches for a decision tree, what kind of feature is favored and chosen first?
point
The feature that increases entropy in the tree nodes.
The feature that splits the data equally into groups.
The feature that increases purity in the tree nodes.
The feature with the greatest number of categories.
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