Under Classify menu in XLMiner, perform k-nearest neighbors classification with all the predictors from columnA (CRIM) to column B (LSTAT) (excluding the MEDV, the MEDV column is the outcome or decision variable for prediction) for both training data set and validation data set, and find the best K for validation data set, trying values of k from 1 to 10 to classify CAT. MEDV (make sure to normalize the data). Also attach the execution result file including confusion matrix, lif chart, and ROC chart in your submission.