[{'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:\n#Hyperparameter tuning\n\nfrom sklearn.model_selection import RandomizedSearchCV,GridSearchCV\n\nparam_grid = {\n              \'n_estimators\':[10, 30, 50, 100,250,500,750,1000,1250,1500,1750],\n              \'max_samples\':[2,4,6,8,10,20,40,60,100],\n              "max_features": [0.5, 1.0],\n              \'n_jobs\':[-2, -1, 1, 2, 3, 4, 5],\n              "bootstrap_features": [True, False]\n             }\n\'\'\'param_grid = {"criterion": ["mae"],\n              "min_samples_split": [10, 20, 40],\n              "max_depth": [2, 6, 8],\n              "min_samples_leaf": [20, 40, 100],\n              "max_leaf_nodes": [5, 20, 100],\n              }\'\'\'\n\nasdf = BaggingRegressor()\n\n\nclf_CC = RandomizedSearchCV(asdf, param_grid )\nclf_Fat = RandomizedSearchCV(asdf, param_grid )\n\nclf_CC.fit(X_train, y_train[\'ConfirmedCases\'])\nclf_Fat.fit(X_train, y_train[\'Fatalities\'])\n\''}, {'role': 'assistant', 'content': "['modelling']"}]