# Analysis and Comparison of Prediction of Heart Disease Using Novel Support Vector Machine and Logistic Regression Algorithm

## Abstract

Aim : prediction of coronary disease using novel support vector machine and comparing its accuracy with logistic regression algorithm. Materials and methods : Two social affairs are proposed for predicting the accuracy( %) of coronary disease. To be explicit, the novel supports vector machine and logistic regression algorithms. Here we take 20 samples each for appraisal and compare. The sample size was calculated using G power with pretest power at 80% and the alpha of 0.05 value. Result : The logistic regression gives better precision (87.82%) than the novel support vector machine(SVM) accuracy (81.30%). Thus the real significance of logistic regression is better than novel support vector machine algorithms. Conclusion: From the result, it might be gathered that logistic regression helps in expecting the coronary sickness with more accuracy to appear differently in relation to novel support vector machine algorithms.

## Imprint

G. Pavithraa, Sivaprasad. Analysis and Comparison of Prediction of Heart Disease Using Novel Support Vector Machine and Logistic Regression Algorithm. Cardiometry; Issue 25; December 2022; p.783-787; DOI: 10.18137/cardiometry.2022.25.783787; Available from: https://www.cardiometry.net/issues/no25-december-2022/machine-and-logistic-regression-algorithm