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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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Advances In Spatial Databases Third International Symposium Ssd 93 Singapore June 1993 Proceedings Lncs 692
Authors: David Abel ,Beng Chin Ooi
1st Edition
3540568697, 978-3540568698
