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A Novel Approach to Predict Diabetes by Using Naive Bayes Classifier

Diabetes can be mentioned as one of the most fatal and constant sicknesses that may cause a arise in the glucose levels. The main target of this experiment is to analyze the database of diabetic patients and to predict the diabetic disease in the early stage. In this proposed system of experiment, Naïve Bayes Classification is used for predicting the diabetes. Information mining is a procedure of extricating data from a dataset and change it into justifiable structure for additional utilization. The information arrangement is diabetic patients informational collection is created by gathering information from clinic storehouse comprises of 1865 occurrences with various qualities. The outcomes show that the proposed novel strategy can foresee the diabetes with higher exactness levels (0.96) than the customary/existing techniques. In this proposed system using Naïve Bayes Classifier, Output will be the Web Interface showing the Outcome of having diabetes or not by taking the input values like Insulin level, age and so on. This increases the accuracy of the system.