A cardiovascular disease is one of the most threatening diseases today. It consists of coronary artery diseases (CAD) like angina and myocardial infarction (heart attack), stroke, hypertensive heart disease etc. To predict these diseases accurately and more effectively, Machine learning algorithms are used. The algorithms used for prediction are Support Vector Machine (SVM), Naïve Bayes, Decision tree, K-Nearest Neighbor, Neural Networks. Support Vector Machine (SVM) algorithm is best among other algorithms and its accuracy is not below 50% in any testing and training dataset. This algorithm has low generalization error and it is also computationally inexpensive. In this system, the attributes of dataset is been reduced to increase the accuracy of prediction. This selected attributes are more significant to predict the disease.


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