Diabetes Prediction Using Supervised Learning Models

About 30 million people in India suffer from diabetes. These patients can be provided with proper treatment if the signs of diabetes are identified early on. This study aims to assess the risk of diabetes among individuals based on parameters such as age, body mass index (BMI), blood glucose level, blood pressure etc. The possibility of an individual suffering from diabetes is predicted using three different machine learning models. The accuracy and F1 score for the predictions of logistic regression, Knearest neighbors and support vector machine model are calculated. These scores are then compared and support vector machine (SVM) model is found to be the most accurate among the three chosen models.