Analysis and Prediction of Diabetes Mellitus using Machine Learning Algorithm Minyechil Alehegn Symbiosis Institute of Technology Pune, Maharashtra, India Minyechil.tefera@sitpune.edu.in Rahul Joshi& Dr. Preeti Mulay Symbiosis Institute of Technology Pune, Maharashtra, India rahulj@sitpune.edu.in, preeti.mulay@sitpune.edu.in Abstract —Data mining techniques (DMTs) are very help full to predict the medical datasets at an early stageto safe human life. Large amount of medical datasets areopen in different data sources which used to in the real world application. Machine learning isa prediction on disease data. Currently, Diabetes Disease (DD) is the leading cause of death over all the world. To cluster and predict symptoms in medical data, various data mining techniques wereused by different researchers in different time. A total of 768 records, data set from PIDD (Pima Indian Diabetes Data Set) which is access from online source. In the proposed system mostknown predictive algorithms areapplied SVM, Naïve Net,DecisionStump, and Proposed Ensemble method (PEM).Anensemble hybrid modelbycombining the individual techniques/methods into one we made Proposed Ensemble method (PEM). Theproposed ensemble method (PEM) provides high accuracy of 90.36% Keywords—collaborative ; Diabetes; classification; Machine learning; Data mining;SVM,; Naïve Net;Decision Stump; PEM I. INTRODUCTION Currently in a global world, there are so many chronic diseases are distributed throughout the world, both in the developing and developed country such serious disease are distributed. From those serious diseases, Diabetes mellitus is one of the chronic diseases in the world which cut human life at early age. Diabetes Mellitus (DM) gets its name by health professionals’ .At this time diabetes disease increases rapidly within the distance of light like Indian countries and some Saharan countries. It is not difficult to guess how much diabetes is very serious and chronic.There are different countries, organization, and different health sectors worry about this chronic disease control and prevent before the person died that means the early presentation of diabetes in order to save human life. Eating is also one factor for diabetes diseases and also, exercise used for healthy even a person live with diabetes the patient can recover from the disease by doing exercise Diabetes diseases have the power or ability to damage different parts of the human being body, from those human body parts which are affected by diabetes are listed as follow:-human heart, human eye, human kidney, and human nerves [39]. As it indicates it is easy to guess how much it is chronic and dangerous diseases that shorts human life. . Tao et al. [2] Algorithms which are used in machine learning have various power in both classification and predicting. Saba et al. [12] there is no single technique gives better performance and accuracy for all diseases, whereas one classifier provides or shows highest performance in a given dataset, another method or approach outdoes the others for other diseases. The new study or the proposed study concentrate on a novel combination or hybridization of different classifiers for diabetes Mellitus (DD) classification and prediction, thus overcoming the problem of individual or single classifiers. The new proposed study follows the different machine learning techniques (MLTs) to predict diabetes Mellitus (DM) at an early stage to save human life. Such algorithms are International Journal of Pure and Applied Mathematics Volume 118 No. 9 2018, 871-878 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu 871