Paper Title
Prediction of Diabetes Mellitus using XG Boost-Gradient Boosting

Diabetes Mellitus is a chronic condition that lasts for life long. Human body is provided with sugar and carbohydrates by conventional food habits. It is mandatory for these sugar and carbohydrates to get broke down into glucose, as glucose acts as a fuel for cells. The glucose is consumed by bloodstream with the help of insulin and it travels into the cells so it can be used as a energy. When pancreas railed at secreting insulin, the disorder called Diabetes Mellitus commences. Formerly, Adaboost algorithm with decision stump is used for prognostication and diagnosis of diabetes. In this paper, we have recouped Adaboost algorithm with Gradient boosting algorithm to hike its veracity from 80.72% to 90%*. Keywords - XGBOOST, gradient boosting; medical data mining; machine leaning; diabetes mellitus; disease prediction model