Cp Based Heart Attack Detection Using Stacking Classifier

Abstract

Heart Disease is one of the foremost common diseases nowadays, and for people that provide health care, it's very necessary to figure out with them to require care of their patients' health and save their life. during this paper, different classifiers were analyzed by performance comparison to classify the guts Disease dataset to classify it correctly and or to Predict heart condition cases with minimal attributes. Large amounts of knowledge that contain some secret information were collected by the healthcare industries. This data collection is beneficial for creating effective decisions. During this case, a Heart Disease Prediction System (HDPS) is developed using Logistic Regression, K Nearest Neighbor, Decision Tree, Random Forest Classifier, and Support Vector Machine algorithms to predict the guts disease risk level.