Machine Learning Algorithms for Preventing and Detecting Diabetes Mellitus

Diabetes mellitus is a group of metabolic disease in which there are high blood sugar levels for a prolonged period. It is because of the pancreas not able to produce enough insulin or the cells of the body do not respond properly to the insulin produced. The symptoms of high blood sugar include frequent urination, increased hunger, etc. If diabetes is left untreated, it may lead to serious complications or even in mortality. The present study gives the machine learning algorithms for preventing and detecting diabetes mellitus. The study uses various enhanced machine learning algorithms such as Gaussian Naïve Bayes algorithm, ridge classifier algorithm, passive aggressive algorithm and MLP classifier algorithm to produce better accuracy score and also gives the better precision, support, F1 score and recall by using confusion matrix. The study also uses standard scalar techniques to scale down the values of dataset. This study also helps us to predict whether the particular patient is diabetic or not.