Comparative Study of Naive Bayes, Gaussian Naive Bayes Classifier and Decision Tree Algorithms for Prediction of Heart Diseases
S A Sushma
Abstract
Nowadays death due to heart disease has been common in the world. It has become a hard task for the medical practitioners to diagnose in the initial stage and requires more expertise and demand in the medical field for prediction. Designing an automated system by using machine learning algorithm will improve the medical efficiency and also reduce the cost. In this paper we are planning to design an automated system that can be used for efficiently predicting the results which give information about the risks need to be faced by the patients with respect to heart diseases by using the parameter available in the dataset. We are extracting the hidden patterns from the parameters by applying data mining techniques. Since the heart data is too massive and complex for analysis using traditional techniques, we are using machine learning algorithm for computation using the parameters available in the dataset and produce accurate prediction of heart disease. Machine Learning Prediction techniques like Naive Bayes Classifier, Gaussian Naïve Bayes Classifier and Decision tree can be used to analyze and predict the heart diseases.