|  | ## Stacking

#### Synopsis

Uses the first inner learner to build a stacked model on top of the predictions of the other inner learners.

#### Description

This class uses n+1 inner learners and generates n different models by using the last n learners. The predictions of these n models are taken to create n new features for the example set, which is finally used to serve as an input of the first inner learner.

#### Input

- training set: expects: ExampleSet

#### Output

- model:

#### Parameters

- keep all attributes: Indicates if all attributes (including the original ones) in order to learn the stacked model.

#### ExampleProcess