An Efficiency of KNN and Decision Tree Techniques for Diabetes Prediction

Blood glucose level is very important in human body function. Energy come human body from food. Blood glucose helped for this process in human body. Diabetes is arise when human body blood glucose level in increased high level. In the health industry data mining and knowledge discovering plays an important role for disease diagnosis, and prediction. Information inside the health industry contains patient records and illness related information. Datamining methods are used for these databases to predict the illness. The purpose is to analyze the effectiveness of Decision tree, KNN and hybrid processes for making predictions hyperglycemia among population. In this work use the KNN and Decision Tree and hybrid methods are applied. The hybrid methods make using decision tree and KNN algorithm. The results showed that Hybrid algorithm gives better results when compared with KNN and Decision Tree.