Data Mining within a Regression Framework

Abstract

Regression analysis can imply a far wider range of statistical procedures than of- ten 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 txees, 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.