[{'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.linear_model import ElasticNetCV, ElasticNet\n\n# Use ElasticNetCV to tune alpha automatically instead of redundantly using ElasticNet and GridSearchCV\nel_model = ElasticNetCV(l1_ratio=[.1, .5, .7, .9, .95, .99, 1], eps=5e-2, cv=10, n_jobs=-1)         \nel_model.fit(X_train, y_train)\nprint(f'Optimal alpha: {el_model.alpha_:.6f}')\nprint(f'Optimal l1_ratio: {el_model.l1_ratio_:.3f}')\nprint(f'Number of iterations {el_model.n_iter_}')"}, {'role': 'assistant', 'content': "['modelling']"}]