-
Book Overview & Buying
-
Table Of Contents
-
Feedback & Rating

Machine Learning for OpenCV
By :

The goal of ensemble methods is to combine the predictions of several individual estimators built with a given learning algorithm in order to solve a shared problem. Typically, an ensemble consists of two major components:
The idea behind ensemble methods has much to do with the wisdom of the crowd concept. Rather than the opinion of a single expert, we consider the collective opinion of a group of individuals. In the context of machine learning, these individuals would be classifiers or regressors. The idea is that if we just ask a large enough number of classifiers, one of them ought to get it right.
A consequence of this procedure is that we get a multitude of opinions about any given problem. So how do we know which classifier is right?
This is why we need a decision rule. Perhaps we consider everybody's opinion of equal importance, or perhaps...