Predicting Heart Disease

• The primary goals of the project were to build accurate predictive models and assess their performance in categorizing heart disease cases.

• Implemented and compared four different machine learning models: Decision Tree, K-Nearest Neighbors (KNN), Support Vector Machine (SVM) ,and Naive Bayes.

• Successfully developed and evaluated the performance of each machine learning model in predicting heart disease using Weka software.

• Provided insights into the strengths and weaknesses of each model.

 

Algorithms Evaluation

Decision Tree

KNN

Naive Bayes

SVM