Voting

In this section, we will try to classify the dataset by using voting ensembles. For our initial ensemble, we will utilize a Naive Bayes classifier, a logistic regression, and a decision tree. This will be implemented in two parts, first by testing each base learner itself and then combining the base learners into an ensemble.

Testing the base learners

To test the base learners, we will benchmark the base learners by themselves, which will help us gauge how well they perform on their own. In order to do so, first, we load the libraries and dataset and then split the data with 70% in the train set and 30% in the test set. We use pandas in order to easily import the CSV. Our goal is to train and evaluate each individual...