[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:from sklearn.tree import DecisionTreeRegressor\nfrom sklearn.linear_model import LinearRegression, Ridge, HuberRegressor, ElasticNetCV\nfrom sklearn.metrics import mean_squared_log_error \nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection import KFold\nfrom sklearn.ensemble import BaggingRegressor, ExtraTreesRegressor, GradientBoostingRegressor, RandomForestRegressor\netr = ExtraTreesRegressor(max_depth= 20, n_estimators= 500)\n#etr.fit(X_train, y_train)\n#Y_to_train = train_sample["count"]\n#X_to_train = train_sample.drop([\'count\'], axis=1)\n\netr.fit(X_train,y_train)\n#y_pred = etr.predict(test_sample)\''}, {'role': 'assistant', 'content': "['modelling']"}]