Heart Disease Detection Using Machine Learning Majority Voting Ensemble Method | IEEE Conference Publication | IEEE Xplore

Heart Disease Detection Using Machine Learning Majority Voting Ensemble Method


Abstract:

This paper presents a majority voting ensemble method that is able to predict the possible presence of heart disease in humans. The prediction is based on simple affordab...Show More

Abstract:

This paper presents a majority voting ensemble method that is able to predict the possible presence of heart disease in humans. The prediction is based on simple affordable medical tests conducted in any local clinic. Moreover., the aim of this project is to provide more confidence and accuracy to the Doctor's diagnosis since the model is trained using real-life data of healthy and ill patients. The model classifies the patient based on the majority vote of several machine learning models in order to provide more accurate solutions than having only one model. Finally, this approach produced an accuracy of 90% based on the hard voting ensemble model.
Date of Conference: 09-11 October 2019
Date Added to IEEE Xplore: 05 December 2019
ISBN Information:
Conference Location: Amman, Jordan

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