concept parallel ensemble method in category machine learning

This is an excerpt from Manning's book Ensemble Methods for Machine Learning MEAP V01. Login to get full access to this book.

We begin our journey into ensemble learning methods in earnest with parallel ensemble methods. We begin with this type of ensemble methods because, conceptually, parallel ensemble methods are easy to understand and implement.

Parallel ensemble methods, as the name suggests, train each component base estimator independently of the others, which means that they can be trained in parallel. As we will see, parallel ensemble methods can be further distinguished as homogeneous and heterogeneous parallel ensembles depending on the kind of learning algorithms they use.

Figure 2.1 Dr. Randy Forrest’s diagnostic process is an analogy of a parallel ensemble method.