[{'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:## parameters\nparams = {\n    "n_estimators": [10, 30, 50, 100],\n    "learning_rate": [.01, 0.1, 0.5, 0.9, 0.95, 1],\n    "random_state" : [42]\n}\n\n## XGBoost Regressor\nAdaBoostR =   AdaBoostRegressor()\nAdaBoostR_grid = GridSearchCV(AdaBoostR, params, scoring=\'r2\', cv=5, n_jobs=-1)\nAdaBoostR_grid.fit(X_train, y_train)\n\n## Output\nprint("Best parameters:  {}:".format(AdaBoostR_grid.best_params_))\nprint("Best score: {}".format(AdaBoostR_grid.best_score_))\n\n## Append to list\nbest_estimators.append(["AdaBoostR",AdaBoostR_grid.best_estimator_])\''}, {'role': 'assistant', 'content': "['modelling']"}]