Analysis of Diabetes dataset, imputing missing values using Random forest and Stochastic Regression Imputation methods, and then imputed dataset is divided into training and test set. Three classification models are trained - KNN, GLM and SVM. Trained models are used to classify test data which has imputed values. All the outputs are compared and discussed.