Diabetes Prediction using Machine Learning

Abstract

Making accurate medical diagnoses requires the discovery of knowledge from medical datasets. Diabetes is frequently referred to as diabetes mellitus (DM) by medical professionals and describes a group of metabolic diseases in which a person has high blood sugar due to insufficient insulin production, improper insulin cell response, or a combination of both. Now is the time to start preventing and early-stage diabetes diagnosis. It is not only a disease but also a cause of many other diseases, including kidney disease, blindness, and heart attacks. The standard diagnostic procedure requires patients to visit a diagnostic facility, consult their doctor, and wait for a day or more to receive their results. Making accurate medical diagnoses requires the discovery of knowledge from medical datasets. Here in our project with the help of classifiers we are predicting if the person is diabetic or not. Each classifier has different accuracy. We came to know by calculating the confusion matrix. By which we found out that the highest accuracy is provided by Logistic Regression classifier i.e.79%.