The technique used for mining the vital data from the pre-existent record known as data mining. It is used for diseases detection at an early stage in medical services. In medical issues, diabetes is a major worldwide problem from various deadliest diseases. “Around 422 million people worldwide are suffering from diabetes”. The purpose of this research is to determine a prototype which can prophesy the possibility with a maximum accuracy of diabetes in patients. So to identify pre-diabetes using two (decision tree and naïve bayes) classification algorithms. The next main focus is to analyze the outcomes and ascertain which technique is more effective and superior from both of them. This paper (pinpointed on) is comparing data mining algorithms which are used for diabetes prognosticate.

Data Mining, Diabetes, Decision Tree, Naïve Bayes, WEKA

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