[{'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:parameters = [{'n_estimators': [100, 200, 300, 400, 500, 600, 700, 800, 900, 1000], \n                     'learning_rate': [0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, \n                                       0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, 0.95, 1.0]\n                    }]\nfrom sklearn.model_selection import GridSearchCV\ngsearch = GridSearchCV(estimator=XGBRegressor(),\n                       param_grid = parameters, \n                       scoring='neg_mean_absolute_error',\n                       n_jobs=4,cv=3)\n\ngsearch.fit(x_train,y)\ngsearch.best_params_, gsearch.best_score_"}, {'role': 'assistant', 'content': 'modelling'}]