[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': "Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:# train model to predict fatalities/day\ndf_train = df_traintest8[(pd.isna(df_traintest8['ForecastId'])) & (df_traintest8['day']<=day_before_public)]\ndf_valid = df_traintest8[(pd.isna(df_traintest8['ForecastId'])) & (day_before_public<df_traintest8['day'])]\ndf_test = df_traintest8[pd.isna(df_traintest8['ForecastId'])==False]\nX_train = df_train[col_var]\nX_valid = df_valid[col_var]\ny_train = np.log(df_train[col_target].values.clip(0, 1e10)+1)\ny_valid = np.log(df_valid[col_target].values.clip(0, 1e10)+1)\ntrain_data = lgb.Dataset(X_train, label=y_train, categorical_feature=col_cat)\nvalid_data = lgb.Dataset(X_valid, label=y_valid, categorical_feature=col_cat)\nnum_round = 15000\nmodel = lgb.train(params, train_data, num_round, valid_sets=[train_data, valid_data],\n                  verbose_eval=100,\n                  early_stopping_rounds=150,)\n\nbest_itr = model.best_iteration"}, {'role': 'assistant', 'content': 'data_preprocessing'}]