COMPARATIVE ANALYSIS OF DATA MINING ALGORITHMS FOR DIABETES LEVEL PREDICTION

Abstract

Diabetes could be a illness that can cause a worldwide wellbeing issue concurring to the universal diabetes league by 2035 382 million individuals around the world will have diabetes and this number will twofold to 592 million the body changes over nourishment into sugar or glucose and at this time our pancreas has to discharge affront which is critical for the release of glucose into cells sort 1 and 2 diabetes are the foremost common  maladies  but  there  are  others  such as gestational diabetes and other maladies that happen amid pregnancy machine learning may be a modern wonder within the writing where machine learning learns from involvement the point of the extend is to combine the comes about of different strategies with machine learning to make a predictive work impact of early diabetes such as k-z closest neighbor calculated relapse back vector machine and irregular timberland utilizing choice trees each calculation calculates the precision of the demonstrate and after that employments the demonstrate with higher individuals from the show to foresee diabetes catch phrase machine learning diabetes choice          tree      k-nearest neighbor calculated relapse bolster vector machine exactness.