[{'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:b"#\\n#param_grid = {\\n#    \'learning_rate\': [0.1, 0.01, 0.001, 0.0001],\\n#    \'n_estimators\': [100, 1000, 1500, 2000, 4000],\\n#    \'max_depth\': [1, 2, 3, 4, 5, 8, 10]\\n#}\\n#\\n#scorer = make_scorer(loss_func, greater_is_better=False)\\n#\\n#gb = GradientBoostingRegressor(random_state=42)\\n#\\n#gbr = GridSearchCV(gb, param_grid, cv=4, scoring=scorer, n_jobs=3).fit(X, Y)\\n#print(\'\\\\tParams:\', gbr.best_params_)\\n#print(\'\\\\tScore:\', gbr.best_score_)\\n\\ngbr = GradientBoostingRegressor(n_estimators=2000, learning_rate=0.01, max_depth=4)\\n\\ngbr.fit(X, Y)"'}, {'role': 'assistant', 'content': "['modelling']"}]