Abstract

In current toiling world cardiovascular diseases is becoming a main cause that affects human survival.  Machine learning algorithms are becoming more popular in the domain of health care. Heart disease contributes to high mortality rates in India for the past years. This study focus on estimating the efficiency of several machine learning models by providing a predictive analysis model for heart disease. Heart disease UCI dataset with 13 different attributes of 303 patients has been utilized and upon which several supervised machine learning algorithms has been applied and their accuracy has been determined. It is concluded that K-Nearest Neighbor and Random forest algorithm shows better accuracy compared to other algorithms.