Data Mining within a Regression Framework
- Richard A. BerkAffiliated withDepartment of Statistics, UCLA
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.
Keywordsregression smoothers splines CART bagging random forests
- Data Mining within a Regression Framework
- Book Title
- Data Mining and Knowledge Discovery Handbook
- Book Part
- pp 231-255
- Print ISBN
- Online ISBN
- Springer US
- Copyright Holder
- Springer Science+Business Media, Inc.
- Additional Links
- random forests
- Industry Sectors
- eBook Packages
To view the rest of this content please follow the download PDF link above.