Supervised Approach of Machine Learning in Medical Diagnosis

Abstract

The medical diagnosis for any disease requires a lot of information if it is diagnosed on the basis of the information provided. This prediction task is a very complex task and therefore the expert system that performs the diagnosis needs to use the best and most suitable Machine Learning algorithm to implement it. This research paper provides the approach in which the supervised Machine Learning technique will be used to perform the classification based diagnosis task. In this paper the primarily available supervised learning based classification algorithms like Naïve Bayes, SVM and Decision tree will be fed with the same data of diabetic patients and their accuracy will be tested. This analysis of algorithms of supervised learning will provide a glimpse of the best algorithm to handle and predict the decision with better accuracy.