Ensemble methods combine predictions of base models in order to improve performance or generalizability over a single model. To this end, there are many approaches that either use averaging or voting over base model predictions. The main objective is to integrate ensemble support for the existing flow of the WSO2 Machine Learner. Implementation will include following tasks: Implement an ensemble method(s), to combine multiple algorithms (particularly Stacking, Boosting and Bagging) Create a UI to include the end to end flow of training the algorithm. Integrate it to the WSO2 Machine Learner.