An iterative 'flip-flop' approximation of the most informative split in the construction of decision trees

Abstract
The authors seek a fast algorithm for finding the best question to ask (i.e., best split of predictor values) about a predictor variable when predicting membership in more than two categories. They give a fast iterative algorithm for finding a suboptimal question in the N category problem by exploiting a fast algorithm for finding the optimal question in the two-category problem. The algorithm has been used in a number of speech recognition applications.

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