[{'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 xgboost import XGBRegressor\nfrom sklearn.preprocessing import LabelEncoder\nle = LabelEncoder()\n\ncountries = X_Train.Country.unique()\n\ndf_out = pd.DataFrame({'ForecastId': [], 'ConfirmedCases': [], 'Fatalities': []})\n\nfor country in countries:\n    states = X_Train.loc[X_Train.Country == country, :].State.unique()\n\n    for state in states:\n        condition_train = (X_Train.Country == country) & (X_Train.State == state)\n       \n        # Get X and y (train)\n        X_Train_CS  = X_Train.loc[condition_train, ['State', 'Country', 'Date', 'ConfirmedCases', 'Fatalities']]\n        y1_Train_CS = X_Train_CS.loc[:, 'ConfirmedCases']\n        y2_Train_CS = X_Train_CS.loc[:, 'Fatalities']\n        X_Train_CS  = X_Train_CS.loc[:, ['State', 'Country', 'Date']]\n\n        # Get X and y (test)\n        condition_test = (X_Test.Country == country) & (X_Test.State == state)\n        X_Test_CS = X_Test.loc[condition_test, ['State', 'Country', 'Date', 'ForecastId']]\n        \n        # Save forcast id for submission\n        X_Test_CS_Id = X_Test_CS.loc[:, 'ForecastId']\n        X_Test_CS    = X_Test_CS.loc[:, ['State', 'Country', 'Date']]\n        \n        model1 = XGBRegressor(n_estimators=1000)\n        model1.fit(X_Train_CS, y1_Train_CS)\n        y1_pred = model1.predict(X_Test_CS)\n        \n        model2 = XGBRegressor(n_estimators=1000)\n        model2.fit(X_Train_CS, y2_Train_CS)\n        y2_pred = model2.predict(X_Test_CS)\n        \n        df = pd.DataFrame({'ForecastId': X_Test_CS_Id, 'ConfirmedCases': y1_pred, 'Fatalities': y2_pred})\n        df_out = pd.concat([df_out, df], axis=0)\n    # Done for state loop\n# Done for country Loop\n\ndf_out.ForecastId = df_out.ForecastId.astype('int')\ndf_out.tail()"}, {'role': 'assistant', 'content': "['modelling']"}]