Decision Tree Classifier

e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science

Volume:03/Issue:03/March-2021 Impact Factor- 5.354 www.irjmets.com

Figure 8: Naïve Bayes The confusion Matrix of the dataset obtained from the Naive Bayesis shown below which provides all the necessary measures of the choice:

9.0 Voting Classifier

A Voting Classifier is a newly introduced scikit-learn machine learning model that trains on numerous models and predicts an output based on their highest probability of chosen category as the output. It merely aggregates each classifier's findings passed into Voting Classifier and predicts the output class based on the highest voting majority. The idea of creating separate models and finding the accuracy for each of them, we make a single model that trains these models and predicts output based on their combined majority voting for each output class.

Figure 9: Voting Classifier