• Ravindar Mogili
• Dr. G.Narsimha
• Mahesh Nagamalla
• Dr. R. Jegadeesan

Analysis of health data helps the doctors in decision making. As the continuously addition of daily generated data, analysis becomes more complicated. Besides this it also requires more memory space and computation time. The analysis process made simple by normalizing huge data, i.e., removing the redundant and useless data for analysis. The Rough Set Attribute Reduction (RSAR) calculates reducts of full set attributes and generate minimal attributes set. This is given as input to the Support Vector Machine. The SVM can analyze diagnosis model of health data and predicts the class of data item, i.e., disease stage. The objective of this paper is to improve classification accuracy of the health data by combining RSAR and SVM.

Medical data, Rough set, Attribute reduction, Support vector Machine, Classification, Heart disease

"Rough Set Attribute Reduction with Support Vector Machine for Prediction of Heart Disease", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.652-656, April-2019, Available :http://www.jetir.org/papers/JETIRAU06100.pdf

"Rough Set Attribute Reduction with Support Vector Machine for Prediction of Heart Disease", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp652-656, April-2019, Available at : http://www.jetir.org/papers/JETIRAU06100.pdf