[{'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 import datasets\nfrom sklearn.linear_model import Ridge\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import mean_absolute_error\nimport optuna\n \ndef objective(trial):\n    params = {\n        \'alpha\': trial.suggest_loguniform("alpha", 0.1, 5), \n        \'fit_intercept\': trial.suggest_categorical(\'fit_intercept\', [True, False]),\n        \'normalize\': trial.suggest_categorical(\'normalize\', [True, False]),\n    }\n \n    reg = Ridge(**params)\n    reg.fit(X_train, y_train)\n    y_pred = reg.predict(X_test)\n \n    mae = mean_absolute_error(y_test, y_pred)\n    return mae\n \''}, {'role': 'assistant', 'content': "['modelling']"}]