Computation Model for Identifying Types of Diabetics Using Multi-SelectionCriteria Evaluation and K-Nearest Neighbor

Abstract

The main purpose of this topic is to develop a dynamic model of a Diabetes solution system Diabetes mellitus is a chronic disease caused by inherited and or acquired deficiency in production of insulin by the pancreas or by the ineffectiveness of the insulin produced such a deficiency results in increased concentrations of glucose in the blood Which in turn damage many of the body systems in particular the blood vessels and nerves Diabetes mellitus often simply referred to as diabetes is a group of metabolic diseases in which a person has high blood sugar either because the body does not produce enough insulin or because cells do not respond to the insulin that is produced This high blood sugar produces the classical symptoms of polyuria frequent urination polydipsia increased thirst and polyphonic increased hunger diabetes is data mining based notification systems This system developed is main purposed the people easily treatment for accommodation This system helps finds diabetes what type of diabetes type1 type2 no diabetes easily provide this system In this work at first identity all the dependent variable or data to classify the suitable from unsuitable location Then I have classified the data using Multi Criteria Evaluation System MCES 2 MCES helped the data set to be properly design and manipulated the system and KNearest Neighbor helped the diabetes range 1 The main purpose of applying this identification is diabetes level The concept of basically helped to build knowledge base Most important of this topics collecting the real data for diabetes information