[{'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:failed_confirmed = []\nfailed_fatalities = []\nconfirmed_popt = {}\nfatalities_popt = {}\n\nfor region in regions:\n    x_data = train_data[region][\'DayNo\']\n    y_ConfirmedCases_data = train_data[region][\'ConfirmedCases\']\n    y_Fatalities_data = train_data[region][\'Fatalities\']\n\n    # Fit data to function\n    try:\n        popt, pcov = curve_fit(sigmoid, x_data, y_ConfirmedCases_data)\n        confirmed_popt[region] = popt\n    except:\n        failed_confirmed.append(region)\n\n    try:\n        popt, pcov = curve_fit(sigmoid, x_data, y_Fatalities_data)\n        fatalities_popt[region] = popt\n    except:\n        failed_fatalities.append(region)\n        \nprint("Failed confirmed: " + str(len(failed_confirmed)))\nprint("Failed fatalities: " + str(len(failed_fatalities)))\nprint("Total: " + str(len(regions)))\''}, {'role': 'assistant', 'content': "['helper_functions', 'comment_only']"}]