Heart-Stroke-Prediction-using-Ensemble-Learning-with-various-ML-algorithms

In this project, we have tried to train different machine learning models - Naive Bayes, Logistic Regression, Decison Tee, Random Forest, SVM and KNN, with the standard dataset related to heart-stroke. In the later part of the project we have tried to improve the accuracy by making a new model. This new model is developed with the help of Ensemble Learning of top perfming models - Naive bayes , logistic Regression, KNN . Further, we found that ensembbling these models with the method of Stacking provided us better accuracy than that of Max Voting or Boosting.