Training, crossvalidation and testing dataset

@@ -221,10 +221,7 @@ if __name__ == "__main__":
                                                           cv=crossV, n_jobs=jobs, verbose=3)
                                                           cv=crossV, n_jobs=jobs, verbose=3)
     elif args.classifier == 'kNN':
     elif args.classifier == 'kNN':
         # kNN
         # kNN
-        classifier = KNeighborsClassifier()
-        paramGrid = {'n_neighbors ': [3, 5, 7]}
-        myClassifier = model_selection.GridSearchCV(classifier, paramGrid,
-                                                          cv=crossV, n_jobs=jobs, verbose=3)
+        myClassifier = KNeighborsClassifier()
     else:
     else:
         print("Bad classifier")
         print("Bad classifier")
         exit()
         exit()