Ensemble Learning Ensemble learning is a machine learning archetype or theory where multiple learners are trained or applied to datasets to solve the same problem by extracting multiple predictions then combined into one composite prediction. It is a process that uses a set of models, each of them obtained by applying a learning process to a given problem. This set of models (ensemble) is integrated in some way to obtain the final prediction.” (Moreira, et al. 2012, 3) This in contrast to ordinary machine learning approaches which try to learn one hypothesis from training data, ensemble methods try to construct a set of hypotheses and combine them to use. It is a powerful way to improve the performance of your model. It usually pays off to apply ensemble learning over…