A Machine Learning Approach for Heart Attack Prediction

Abstract

AbstractThere are lot of activities in the human body which are unpredictable in general form. Heart attack is one of them, and it is so serious activity in human body which cause in death of human. But this action gives some sim-terms before it committed. Although it is not highly noticeable in normal conditions, it committed suddenly. So this is one of the highly unpredictable occurrences in human body. With the technology advancement some of the data mining algorithms were developed to predict the heart attack. In such continuation, different data mining algorithms, with machine learning approach are able to predict heart attack occurrence in human body. It is one of the typical diagnosis tasks, but it should be achieved accurately and efficiently with the help of machine learning. The present research paper is an attempt to model and solve the heart attack prediction problem. Different machine algorithms such as KNN, SVC, RFC, decision tree and logistic regression are taken here to form a model for the study. The forte of the projected model is sufficient and is competent enough to predict the occurrence of heart attack in the human body by the compilation of some sim-terms occurring in the body. So machine learning approach is a good approach to predict occurrence of heart attack timely and we may go for proper treatment and precaution for the same.KeywordsMachine learningData miningAlgorithmDecision treeKNN