Performance Analysis of Heart Disease Prediction System using Machine Learning Approach

Heart disease is becoming the leading cause of death in worldwide. In today’s world due to work load and changes in the human lifestyle lead to many diseases. Early detection of any disease prevents human life and save it from other damage also, artificial intelligence techniques provide the greatest results for every sector, health care or medical science is one of them. In this paper, we present cardiovascular disease prediction using machine learning techniques such as logistic regression, random forest, and k-nearest neighbor classifier, our result shows that better than existing techniques, here results are evaluated in the form of quality of performance parameters measured such as accuracy, precision, recall, and F1-score, all the results are based on respective confusion matrix which is based on some parameters like true positive rate, false positive rate, true negative rate, and false negative rate