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.
-
Notifications
You must be signed in to change notification settings - Fork 0
In this project, different supervised machine learning algorithms like Decision Tree, Naive Bayes, K-nearest neighbour,Random Forsest, Logistic Regression etc. were trained on the training data set and then Ensemble Learning was used to improve the accuracy were
Aryan0199/Heart-Stroke-Prediction-using-Ensemble-Learning-with-various-ML-algorithms
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
In this project, different supervised machine learning algorithms like Decision Tree, Naive Bayes, K-nearest neighbour,Random Forsest, Logistic Regression etc. were trained on the training data set and then Ensemble Learning was used to improve the accuracy were
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published