A Comparative Study of CN2 Rule and SVM Algorithm and Prediction of Heart Disease Datasets Using Clustering Algorithms

Ramaraj. M, Antony Selvadoss Thanamani


In this paper, we discuss diagnosis analysis and identification of heart disease using with data mining techniques. The heart disease is a major cause of morbidity and mortality in modern society; it is extremely important but complicated task that should be performed accurately and efficiently. It is an huge amount data of leads medical data to the need for powerful data analysis tools are availability on the data mining technique. They have long to been an concerned with applying for statistical and data mining tools and data mining techniques to improve data analysis on large datasets. In this paper, to proposed system are implemented to find out the heart disease through as to compared with the some data mining techniques are Decision tree, SOM, CN2 Rule and K-Means Clustering the data mining could help in the identification or the prediction of high or low risk of Heart Disease.Keywords: Data Mining, Heart Disease, Decision tree, SOM, CN2 Rule and cluster.

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ISSN (Paper)2224-610X ISSN (Online)2225-0603

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