I’m working on a Science question and need guidance to help me study.
A popular data mining method that is used to classify a dependent categorical variable based on measurements of one or more predictor variables is classification decision trees. Explain how does the decision tree algorithm pick the attributes for splitting. Why is tree pruning useful in decision tree induction? What is a drawback of using a separate set of data to evaluate pruning?
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