Predicting-Diabetes-using-RFClassification

In Arizona and Mexico, women above 21 years, belonging to the Pima Indian Heritage, are most likely to be diabetic. We obtain a dataset of the same (consisting of 769 entries) from Kaggle. We try to use Random Forest Classification in order to predict whether a given person with some measured medical parameters, is likely to be diabetic or not.