A implementation approach for diagnosis of diabetes type II foot ulcer using R in data mining

Abstract Data mining approach helps to analyze patient diseases. Diabetes Mellitus is a chronic disease to affect various organs of the human body. Early prediction can save human life and can take control over the diseases. The present work emphases on analysis of diabetes through decision tree algorithm with statistical implication using R. Diabetes is a common disease with all age group on the world . The main aim of this research paper is to study and discuss about the decision tree implementation using R with different kinds of medical datasets. For classification is performed by decision trees in R. This paper will help for early detection of the complications which might help in timely treatment of individuals. For data preprocessing the real time medical data set used Manual, R Studio and WEKA tool. Keywords : Data Mining, Classification, R, R Studio , SVM , Decision Tree, Accuracy rate and KNN.