A 6-fold cross-validation approach was employed during the model development process. The results indicated that the decision tree algorithm achieved the highest accuracy in predicting heart disease.
Logistic Regression Model Accuracy 0.8688524590163934
Logistic Regression Model Accuracy 0.8688524590163934
Accuracy score of Decision Tree model= 0.8032786885245902
Accuracy score of RandomForest model= 0.8360655737704918
Accuracy score of Gradient Boosting Classifier model= 0.8360655737704918
Accuracy of Guassian Naive_bayes 0.8524590163934426
