Predicting Diabetes u sing SVM Implemented by Machine Learning

Age, BMI, and insulin levels, which play important roles because they are not constant do follow any specific patterns, some of the factors that can be used to identify chronic disease Diabetes. Besides elements described above, a few additional will studied in subsequent subjects this study. Before cleaning data, support vector machine (SVM) algorithms, pandas, NumPy, sci-kit-learn libraries predict patient's diagnosis classify data into various categories. The output contains two parameters: DIABETIC NON-DIABETIC. With available dataset, accuracy score training was 77.5 percent test 80.5 percent.