Dentistry
3 years ago

Revolutionizing Heart Disease Prediction: Decision Tree Algorithm Outperforms Naive Bayes

2022 International Conference on Business Analytics for Technology and Security (ICBATS)
Improving the Accuracy for Prediction of Heart Disease by Novel Feature Selection Scheme using Decision tree comparing with Naive-Bayes Classifier Algorithms
S. K. L. Sameer, P. Sriramya

Paper Summary

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The goal of the study was to improve the accuracy of predicting heart disease by using a combination of Decision Tree and Naive Bayes algorithms. The researchers found that the Decision Tree algorithm performed better than the Naive Bayes algorithm in predicting heart disease, with a 90.16% higher accuracy rate. This suggests that the Decision Tree method is more effective in identifying heart disease compared to the Naive Bayes method.