DIABETIC DISEASE PREDICATION USING MACHINE LEARNING TO ACCOMPLISH PRECISE ACCURACY

Abstract

Now a day’s the working environments has turned out to be stressful due to numerous reasons. These things make a drastic raise to various chronically diseases irrespective of age, gender and other relevant conditions. No one is aware or can give assurance that they will be safe and healthy for the next moment. One such kind of disease we have considered to discuss as a case study is diabetic due to which the death rates are increasing drastically throughout the globe. To be safe and to carry out a good life it is advised to trace out the probability of coming across through such kind of diseases.  With drastic new cutting edge technologies surrounding us it is possible to predict the possibility or probability of occurrence of such kind of diseases with certain parametric symptoms which are associated with these diseases. Among many such categories of diseases we have chosen the prediction of diabetes at an early stage based on the symptoms. In this paper we have used ML techniques for our early prediction with accurate accuracy.

Keywords: Decision Tree, Gradient Boosting, Gaussian Naive Bayes, Linear Regression, K-Nearest Neighbours, Machine Learning,  Random Forest, Support Vector Clustering.