Library is missing Stacked Ensemble

[andrewdalpino]

Out of the 4 major ensemble methods (boosting, bagging, voting, and stacking), Rubix only implements 3. Stacking is similar to a voting committee, however the influences are learned by a separate learner such as Linear or Logistic Regression. The Rubix architecture allows for a Meta Estimator implementation such that the notion of a Model Orchestra can be generalized to classification and regression. As stacking has been shown in data competitions to be crucial for the best possible accuracy scores, the benefit to Rubix engineers will be high.

The general idea is we have an orchestra of estimators that each become the input features to a final estimator (conductor) that makes the final prediction. Since the Rubix architecture allows for the concept of a Meta Estimator, the implementation would be general to both classifiers and regressors.

[andrewdalpino]

Implemented as Model Orchestra meta estimator