Abstract

The objective of our paper is to predict the chances of diabetic patient getting heart disease. In this study, we are applying Naïve Bayes data mining classifier technique which produces an optimal prediction model using minimum training set. Data mining is the analysis step of the Knowledge Discovery in Databases process (KDD). Data mining involves use of techniques to find underlying structures and relationships in a large database. Diabetes is a set of related diseases in which body cannot regulate the amount of sugar specifically glucose (hyperglycemia) in the blood. The diagnosis of diseases is a vital role in medical field. Using diabetic’s diagnosis, the proposed system predicts attributes such as age, sex, blood pressure and blood sugar and the chances of a diabetic patient getting a heart disease.

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