A Data Mining Approach for the Diagnosis of Diabetes Mellitus using Random Forest Classifier

Abstract

Diabetes mellitus is an interminable disease that forces excessively high human, social and financial expenses for a nation. Additionally, minimizing its commonness rate and in addition its excessive and risky confusions requires viable administration. Diabetes administration depends on close participation between the patient and health awareness experts. Data mining gives a diversity of methods to investigate large data keeping in mind the end goal to find hidden knowledge. This study is an effort to plan and execute a descriptive data mining approach and to devise association standards to envisage diabetes behaviour in arrangement with particular life style parameters, including physical activity and emotional states, especially in elderly diabetics. Proposed methodology is based on Random Forest Classifier. General Terms Medical Data mining, Classification using Random Forest Classifier.