[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': "Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:from sklearn.cross_validation import StratifiedKFold\nkfold = StratifiedKFold(y=y_train, n_folds=10, random_state=1)\nscores = []\nfor k, (train, test) in enumerate(kfold):\npipe_lr.fit(X_train[train], y_train[train])\nscore = pipe_lr.score(X_train[test], y_train[test])\nscores.append(score)\nprint('Fold: %s, Class dist.: %s, Acc: %.3f' % (k+1,\nnp.bincount(y_train[train]), score))\nprint('\\nCV accuracy: %.3f +/- %.3f' % (np.mean(scores), np.std(scores)))"}, {'role': 'assistant', 'content': 'evaluation'}]