Decision Trees

This chapter describes about the classification methods for data mining. The method involves the construction of a decision tree, a collection of decision nodes, connected by branches, extending downward from the root node until terminating in leaf nodes. Decision rules can be constructed from a decision tree simply by traversing any given path from the root node to any leaf. The complete set of decision rules generated by a decision tree is equivalent to the decision tree itself. The decision trees produced by classification and regression trees (CART) are strictly binary, containing exactly two branches for each decision node. CART recursively partitions the records in the training data set into subsets of records with similar values for the target attribute. The CART algorithm grows the tree by conducting for each decision node, an exhaustive search of all available variables and all possible splitting values by selecting the optimal split.