[{'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:#LightGBM\n\nparams = {"objective" : "rmse",\n          "boosting" : "gbdt", \n          "metric" : "rmse",\n          "num_iterations" : 7500,\n          "top_k" : 30, \n          "max_depth" : 8, \n          "num_leaves" : 800, \n          "min_data_in_leaf" : 20, \n          "learning_rate" : 0.02,\n          "bagging_fraction" : 0.7, \n          "bagging_seed" : 3,\n          "bagging_freq" : 5, \n          "feature_fraction" : 0.5, \n          "num_threads" : 4\n         }\n\ndataset_params = {"max_bin" : 200, \n                  "min_data_in_bin" : 3 \n                 }\nlgb_train = lgb.Dataset(X_train, label=y_train[\'SalesLog\'], params=dataset_params)\nmodel = lgb.train(params, lgb_train, verbose_eval=50, keep_training_booster=True)\''}, {'role': 'assistant', 'content': 'modelling'}]