Identification of diseases are very challenging task in field of medical science. Heart disease is very critical issues facing by the people. In our proposed work we have used data mining based classification techniques for analysis and classification of different level of heart disease namely Cleveland, Switzerland, Hungarian and Long Beach. We have used WEKA and Rapid miner data mining tools for analysis of heart disease data set and compared the performance of different classification techniques with four heart disease data set using WEKA and Rapid Miner data mining tool. The proposed SVM gives better accuracy as 66.67% with Hungarian data set in case of WEKA data mining tool while Decision Stump gives better accuracy as 63.94% with same Hungarian data set in case of Rapid miner data mining tool. The Hungarian data set gives better performance with our proposed data mining tools and classification techniques which can help the people to predict effective factors about Coronary Heart Disease
