A word about ensemble models
Before we start diving into the algorithms, there is an important modeling concept that you should be aware of, known as ensemble. The term ensemble is used to describe methods that use multiple algorithms to create a model.
For example, instead of creating just one model to predict fraudulent transactions, you could create multiple models that do the same thing and, using a vote sort of system, select the predicted outcome. The following table illustrates this simple example:
Figure 7.2 – An example of a voting system on ensemble methods
The same approach works for regression problems, where, instead of voting, we could average the results of each model and use that as the final outcome.
Voting and averaging are just two examples of ensemble approaches. Other powerful techniques include blending and stacking, where you can create multiple models and use the outcome of each model as features for a main model. Looking...
