Training, crossvalidation and testing dataset

@@ -219,13 +219,13 @@ if __name__ == "__main__":
         paramGrid = {'alpha': scipy.stats.expon(scale=1.0)}
         myClassifier = model_selection.RandomizedSearchCV(classifier, paramGrid, n_iter=nIter,
                                                           cv=crossV, n_jobs=jobs, verbose=3)
-    elif args.classifier == 'kNN':
-        # kNN
-        k_range = list(range(1, 7, 2))
-        classifier = KNeighborsClassifier()
-        paramGrid = {'n_neighbors ': k_range}
-        myClassifier = model_selection.RandomizedSearchCV(classifier, paramGrid, n_iter=3,
-                                                          cv=crossV, n_jobs=jobs, verbose=3)
+    # elif args.classifier == 'kNN':
+    #     # kNN
+    #     k_range = list(range(1, 7, 2))
+    #     classifier = KNeighborsClassifier()
+    #     paramGrid = {'n_neighbors ': k_range}
+    #     myClassifier = model_selection.RandomizedSearchCV(classifier, paramGrid, n_iter=3,
+    #                                                       cv=crossV, n_jobs=jobs, verbose=3)
     else:
         print("Bad classifier")
         exit()