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

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Decision Tree

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KNN

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Naive Bayes

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SVM

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