A COMPARATIVE ANALYTICS OF SVM DT NB CLASSIFIER FOR HEART DISEASE PREDICTION IN ML ALGORITHMS
International Research Journal of Modernization in Engineering Technology and Science · 2023
Heart disease prediction is a crucial task in the field of medical diagnosis.Machine learning algorithms can be used to predict heart disease accurately and efficiently.In this research paper, we present a comparative analysis of three popular machine learning classifiers: Support Vector Machines (SVM), Decision Trees (DT), and Naive Bayes (NB), for heart disease prediction.We evaluate the performance of these classifiers using the Cleveland heart disease dataset.The results show that SVM performs better than DT and NB in terms of accuracy and AUC-ROC score.However, DT has a better F1 score than SVM and NB.Our study provides useful insights into the performance of these classifiers for heart disease prediction.