[{'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:# It is undeniable that working days have a distinct behavior on their own. So we assume that the separation non working days vs working days is a valid one. However,\n# Looking at the non working days the conclusion is less obvious. We will assume that for seasons 3 and 4 we have a distinct pattern for non working days and leave a \n# possible refinement to a later version. Lets see if we can find a separation for weekends and public holidays for seasons 1 and 2.\n\n# In what follows we will repeat the steps above but now, instead of X_train we will have X_holiday_1, instead of X_workingday_1 we will have X_1_public_holidays \n# and X_1_weekends instead X_holiday_1. And the same for season 2. We try to figure out if this separation will increase the ration mean counts /std counts at least\n# for one of these groups'}, {'role': 'assistant', 'content': "['helper_functions']"}]