Diabetes Diagnosis Using Supervised Learning Technique

Abstract

In this paper, an analysis of variables related with diabetes detection is done, using a decision tree which is a kind of algorithm of automatic supervised nonparametric learning, and that is used for classifying tasks from a set of classified objects, each described by an attribute vector and a class label. The classifying objects that have known class label are taken as example to train a mathematical model able to predict the class labels of new objects that have not been classified yet.