ABSTRACT
In recent years, machine learning (ML) has been an advanced technology in the field of medical science. In health care, ML algorithms are used for numerous purposes. The major application of ML is to envision the large data. In this proposed study, we review a heart disease dataset for the early prediction of heart disease. The dataset has 270 instances and 14 attributes. According to existing studies, the researchers have used many ML classifiers (such as support vector machine, K-nearest neighbor, naive Bayes, decision tree, and LR) to predict the heart disease. This dataset is taken from the UCI ML repository. This chapter reviews different ML techniques and their applications and their accuracy results.
