[{'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:t_cas = np.zeros((t_casual.shape[0]-(24*time_steps_cas), time_steps_cas, t_casual.shape[1]))\nt_reg = np.zeros((t_registered.shape[0]-(24*time_steps_reg), time_steps_reg, t_registered.shape[1]))\ncc = 0\ncr = 0\nfor year in [2011,2012]:\nfor i in np.arange(1,13):\nrs = reshape_pred(t_casual[(t_casual[\'year\']==year) & (t_casual[\'month\']==i)].values, time_steps_cas)\ncc += len(rs)\nt_cas[cc-len(rs):cc] = rs\nrs = reshape_pred(t_registered[(t_registered[\'year\']==year) & (t_registered[\'month\']==i)].values, time_steps_reg)\ncr += len(rs)\nt_reg[cr-len(rs):cr] = rs\nt_cas_scaled = np.zeros((t_cas.shape))\nt_reg_scaled = np.zeros((t_reg.shape))\nfor i in np.arange(len(t_cas)):\nt_cas_scaled[i] = scaler_cas.transform(t_cas[i])\nt_reg_scaled[i] = scaler_reg.transform(t_reg[i])\ntest_pred_registered = kr_registered.predict(t_reg_scaled)\ntest_pred_registered[test_pred_registered < 0] = 0\ntest_pred = test_pred_casual + test_pred_registered\nstr_prediction = "datetime,count\\n"\nfor i in range(0, len(test_pred)):\ndatetime = df_test[\'datetime\'][i]\npred = int(round(test_pred[i]))\nstr_prediction += "{},{}\\n".format(datetime, pred)\nf = open(\'pred_keras_gru.csv\',\'w\')\nf.write(str_prediction)\nf.close()'}, {'role': 'assistant', 'content': "['data_preprocessing', 'prediction', 'save_results']"}]