Diabetes Prediction using different Machine Learning Classifiers

Diabetes is a persistent medical condition caused due either when pancreas doesn't secrete as much insulin as the body needs or the body is unable to use insulin efficiently. Diabetes greatly increases the risk of many heart diseases. Early diabetes diagnosis can result in more effective therapy. This paper proposes a method to predict diabetes using different machine learning algorithm methods. The accuracy obtained after using different machine learning models, that is Logistic Regression, KNN, Naive Bayes, SVM, Decision Tree and Random Forest, has been compared.