This article provides an introduction to ensemble statistical procedures as a special case of algorithmic methods. The discussion begins with classification and regression trees (CART) as a didactic device to introduce many of the key issues. Following the material on CART is a consideration of cross-validation, bagging, random forests, and boosting. Major points are illustrated with analyses of real data.
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Richard A. Berk (2006) studied this question.
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