Comparative Analysis of Multiple Classification Algorithms on Heart Disease Prediction

Authors

  • Harshitha M, Sanju V

Abstract

Heart disease is one of the main problem caused among the global group of people. It is one of the leading reasons of demise in the large group of middle aged population. It is essential to have a framework which could efficaciously recognize the coronary heart aliment in lot of samples at once. The proposed algorithms used in our work is  (NB) Naive Bayesian, (DT) Decision Tree, (KNN) K-nearest neighbor, (ANN) Artificial Neural Networks, in predicting coronary heart disease. These algorithms can provide the likeliness of patients getting coronary heart problems. Few of the performance factors used in predicting heart disease are by using the factors Accuracy, Precision, Recall, F1-Score. In our work, we majorly focus on identifying the most efficient algorithm among the DT, NB, KNN and ANN.

Downloads

Published

2020-05-12

Issue

Section

Articles