There is an uncontrolled increase in the rate of heart strokes at adolescent ages. So we must develop a system which will detect the symptoms of heart attack priorly to prevent it. Common man could not have enough money to pay for tests like ECG etc. thus there is a need to provide an automated system which is consistently good in performance. Based on various attributes like age, sex, resting blood sugar etc. We proposed an approach that will be mainly designed to predict the occurrence of heart disease in a person. Machine learning algorithms such as K-Nearest Neighbours is used in the proposed system. Also various ML algorithms like Logistic Regression, Random Forest, Naïve Bayes, K-Means, Decision tree, Support Vector Machine (SVM) are taken into consideration and compared among themselves based on their accuracy rate.
Volume 12 | Issue 2
Pages: 873-878
DOI: 10.5373/JARDCS/V12I2/S20201108