Machine Learning based Diabetes Prediction using Decision Tree J48
A. Mary Posonia, S. Vigneshwari, D. Jamuna Rani
Abstract
Gestational diabetes is found among majority of the Indian pregnant women, when un-attended may give birth defects to child. Diabetes, which is caused by the rise in level of glucose in blood, has many latest devices to identify from blood samples. Diabetes, when unnoticed may bring many serious diseases like heart attack, kidney disease. In this way there is a requirement for solid research and learning models enhancement in the field of gestational diabetes finding and analysis. This research work has proposed a machine learning knowledge, for example, Decision Tree J48 calculation for diabetes forecast. Decision Tree is one of the powerful classification models. The dataset considered of 768 patients data with major 8 features and a target column with result "Positive" or "Negative". Experiment is done with weka, outcome of our demonstration shows that Decision Tree J48 calculation gives more efficiency with less processing time.