Classification of Diabetic Disorder using Machine Learning Approaches

Diabetes is a serious metabolic condition that can affect the entire body. Untreated diabetes raises the risk of heart stroke, diabetes, and other conditions. Millions of individuals are impacted by this disease around the globe. A chronic illness like diabetes may have an effect on world health. In Accordance to the International Diabetes Federation, 382 million people suffer from diabetes all over the world. This would increase to 592 million by 2035. High blood glucose levels cause diabetes, also referred to as diabetes mellitus. Numerous conventional methods based on physical and chemical investigations can be used to diagnose diabetes. Maintaining a healthy lifestyle requires early diabetes identification. Mechanical studies are a potential technique that can aid in early disease diagnosis and assist medical professionals in making diagnoses. Our goal is to use the Scikit-learn tool to develop a classification model that uses the KNN, MLP, SVM, RFC, and CART algorithms to predict diabetes.