Diabetes is the major disorder occurs due to the lack of produce insulin in the body among human being. All types of diabetes can lead to complications in many parts of the body and can increase the overall risk of dying prematurely. The risk of diabetes is increasing day by day and is found mostly in women than men. The very dangerous disease in medicinal field is diabetes disease which is affected for many peoples in popular countries like India. The diagnosis of diabetes is a tedious process. So with improvement in science and technology it is made easy to predict the disease. The purpose is to diagnose whether the person is affected by diabetes or not using Random Forest (RF) Classification Algorithm. The diabetes dataset is a taken as the training data and the details of the patient are taken as testing data. The training data are classified by using the RF classifier and secondly the target data is predicted. RF algorithm used here would be more efficient for both classification and prediction. The results are analyzed with different values for the parameter k.
