Heart disease prediction model with k-nearest neighbor algorithm

Tssehay Admassu Assegie

Abstract


In this study, the author proposed k-nearest neighbor (KNN) based heart disease prediction model. The author conducted an experiment to evaluate the performance of the proposed model. Moreover, the result of the experimental evaluation of the predictive performance of the proposed model is analyzed. To conduct the study, the author obtained heart disease data from Kaggle machine learning data repository. The dataset consists of 1025 observations of which 499 or 48.68% is heart disease negative and 526 or 51.32% is heart disease positive. Finally, the performance of KNN algorithm is analyzed on the test set. The result of performance analysis on the experimental results on the Kaggle heart disease data repository shows that the accuracy of the KNN is 91.99%

Keywords


Automated diagnosis; Disease prediction; Heart disease prediction; KNN classifier; KNN model

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DOI: http://doi.org/10.11591/ijict.v10i3.pp225-230

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