Hands-On Ensemble Learning with R

Chapter 1. Introduction to Ensemble Techniques

Ensemble techniques are model output aggregating techniques that have evolved over the past decade and a half in the area of statistical and machine learning. This forms the central theme of this book. Any user of statistical models and machine learning tools will be familiar with the problem of building a model and the vital decision of choosing among potential candidate models. A model's accuracy is certainly not the only relevant criterion; we are also concerned with its complexity, as well as whether or not the overall model makes practical sense.

Common modeling problems include the decision to choose a model, and various methodologies exist to aid this task. In statistics, we resort to measures ...