[{'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:def clean_data_values(data):\nimp = Imputer(missing_values=\'NaN\', strategy=\'mean\', axis=0)\nimp.fit(data)\nimp_data = imp.transform(data)\nreturn imp_data\ndef model_rfc(data, target, estimators_nbr, n_iter_search, joblib_dump_name):\nclf = RandomForestClassifier(n_estimators=estimators_nbr)\nparam_dist = {"max_depth": [3, None],\n"max_features": sp_randint(1, 11),\n"min_samples_split": sp_randint(1, 11),\n"min_samples_leaf": sp_randint(1, 11),\n"bootstrap": [True, False],\n"criterion": ["gini", "entropy"]}\nrandom_search = RandomizedSearchCV(clf, param_distributions=param_dist, n_iter=n_iter_search,\nscoring=\'recall_weighted\')\nrandom_search.fit(data, target)\njoblib.dump(clf, joblib_dump_name)\nreturn random_search\ndef predict(model, test_data):\nresults = model.predict(test_data)\nreturn results'}, {'role': 'assistant', 'content': 'modelling'}]