Early Stage Diabetes Prediction of Patients in Big Data Healthcare Using Sophisticated Machine Learning Approach

Diabetes is an illness caused because of high glucose level in a human body. Diabetes should not be ignored if it is untreated then Diabetes may cause some major issues in a person like: heart related problems, kidney problem, blood pressure, eye damage and it can also affects other organs of human body. Diabetes can be controlled if it is predicted earlier. To achieve this goal this project work will do early prediction of Diabetes in a human body or a patient for a higher accuracy through applying, Various Machine Learning Techniques. Machine learning is an emerging scientific field in data science dealing with the ways in which machines learn from experience. The aim of this project is to develop a system which can perform early prediction of diabetes for a patient with a higher accuracy by combining the results of different machine learning techniques. In this work, Boosting decision tree model (BDT) is used to predict the diabetes. The proposed model is used boosting algorithm to enhance the perform ace of the model. The accuracy is different for every model when compared to other models. The Result shows that the proposed model achieved higher accuracy compared to other machine learning techniques.