ABSTRACT

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field.After presenting background and terminology, the book cover

chapter 1|22 pages

Introduction

chapter 2|24 pages

Boosting

chapter 3|20 pages

Bagging

chapter 4|32 pages

CombinationMethods

chapter 5|20 pages

Diversity

chapter 6|16 pages

Ensemble Pruning

chapter 7|22 pages

Clustering Ensembles

chapter 8|30 pages

Advanced Topics

8.1.1 Usefulness of Unlabeled Data