Early Diabetics Prognosis Prediction System Adhering to Data Science Utilization Techniques

Early diabetic prognosis is carried out for the age group between 10 -30 years. To predict the diabetic in early stage we consider the following parameters like Cholesterol, BMI, Blood pressure, Blood glucose levels, Gender, Height, and Weight. On calculating the average values of the parameter, we use random forest algorithm to revert the classified data set with an accurate value for prediction. Since the human body can able to transform the intake of the food in the form of glucose which may affect the diabetic parameter value so the keen observation of the value of the diabetic’s parameter must be concentrated. The induction of machine algorithm uses the Uni-variant and Bi-variant variables for the processing of the data. Additionally, support vector classifier (SVC) is used for the unique classification of data set with respect to the diabetic parameters.