An implementation of Ensemble Learning that uses (Weighted) Majority Voting.
The goal of this project is to implement an Ensemble Classifier that uses the Majority Voting and Weighted Majority Voting Techniques in order to combine several classifiers in one.
The resulting program will be evaluated on a number (~15) of heterogeneous datasets and several metrics will be provided to show its performances.
This project is part of the Machine Learning course @ Technische Universität Wien.