Data Mining and Knowledge Discovery Handbook

pp 231-255

Data Mining within a Regression Framework

  • Richard A. BerkAffiliated withDepartment of Statistics, UCLA

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Regression analysis can imply a far wider range of statistical procedures than often appreciated. In this chapter, a number of common Data Mining procedures are discussed within a regression framework. These include non-parametric smoothers, classification and regression trees, bagging, and random forests. In each case, the goal is to characterize one or more of the distributional features of a response conditional on a set of predictors.


regression smoothers splines CART bagging random forests