This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applica

This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applica

1. Introduction to pattern classification. 1.1. Pattern classification. 1.2. Induction algorithms. 1.3. Rule induction. 1.4. Decision trees. 1.5. Bayesian metho

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurat

An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications