Handbook of Statistics

Chapter 5

Bagging, Boosting, and Random Forests Using R

Hansen Bannerman-Thompson¹, M. Bhaskara Rao¹ and Subramanyam Kasala²,    ¹Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45267, USA, ²Department of Mathematics and Statistics, University of North Carolina, Wilmington, NC 28403

Abstract

Huge data sets are a fact of life. An impressive amount of research has been evolving with the advent of rising power of computing to extract information and signals from large noisy data. The purpose of this article is to present some machine learning tools and explain how open source software like R can be used to do your bidding. The reader needs only a rudimentary knowledge of Statistics and R. It is assumed that the reader ...