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The increasing use of computers in statistics has spawned a new generation of multivariate statistical techniques. Chief among these is a tree-structured approach to classification and regression analysis. The CART, or Classification and Regression Trees, program implements a recursive partitioning procedure based on an iterative search for best binary "splits" of data. Resultant classifiers consist of binary trees whose leaves determine class labeling. Extensive use of data resampling techniques replaces biased classifier performance measures.
Grajski et al. (Mon,) studied this question.