A Survey of Data Mining Techniques on

Comparison of classification techniques in Data mining to find the best technique for creating risk prediction model of heart disease at minimum effort. In Data mining, different methods used to find risk prediction of heart disease. There are two types of model used in analysis of data. First one is applying single model to various heart data and another one is applying combined model to the data. The combined model also known as hybrid model. This paper provides a quick and easy understanding of various prediction models in data mining and helps to find best model for further work. This is unique approach because various techniques listed and expressed in bar chart to understand accuracy level of each. These techniques are chosen based on their efficiency in the literature. In previous studies of different researcher expressed their effort on finding best approach for risk prediction model and here we found best model by comparing those researcher’s findings as survey. This survey helps to understand the recent techniques involved in risk prediction of heart disease at classification in data mining. Survey of relevant data mining techniques which are involved in risk prediction of heart disease provides best prediction model as hybrid approach comparing with single model approach. *Author for correspondenc