Performance analysis of machine learning models for prediction of diabetes
Anuj Mangal, Vinod Kumar Jain
Abstract
Machine Learning is an emerging technology in artificial intelligence and computer science. Lot of researchers are applying Machine Learning (ML) models for solving various problems. Disease prediction using machine learning is a very hot area of research for many researchers. Diabetes is one of the major medical problems in common people. Because of improper life style and bad eating habits of people, this disease is increasing with a very high speed and affecting a lots of people throughout the world. It is very difficult to predict the chances of diabetes in human being with the help of existing methods and medical tests. Machine learning algorithms can be trained on a data set of the people or patients and then the trained model can be used in early prediction of diabetes in a person based on his or her medical symptoms. This paper applied the power of ML algorithms and implement two most commonly used ML models for diabetes prediction. After the experiment we are able to predict the diabetes by achieving 99% accuracy using random forest machine learning algorithm.