A Multilayer Perceptron Neural Network Model For Predicting Diabetes

Abstract

Diabetes is a silent metabolic disorder that affects a huge number of people all over the world. It affects
the entire body system badly and can create many complications in the body if unidentified. One of the
main reasons for the increase in the number of people getting affected by this disease nowadays is the
lifestyle of the people. Today, the majority of us live a life that is characterized by less physical activity
coupled with the consumption of lots of junk food. In such a scenario, it becomes critical to identify this
disease at the earliest. For the same, this study proposes a machine learning model based on Multilayer
Perception Neural Network (MLP), which can identify diabetes patients. Apart from MLP, the 5-fold crossvalidation is also applied to get better results on test data after training. The experiment results of the model
show 82% accuracy in prediction, which is quite better. The results of the proposed model are also
compared with some existing state of arts.