[{'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:#Make ML Models\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.linear_model import Lasso\nfrom sklearn.linear_model import Ridge\nfrom sklearn.linear_model import ElasticNet\nfrom sklearn.ensemble import RandomForestRegressor\nfrom xgboost import XGBRegressor\n\nml_models = {\n    'LinearRegression': LinearRegression(),\n    'LassoRegression': Lasso(),\n    'RidgeRegression': Ridge(),\n    'ElasticNet': ElasticNet(),\n    'RandomForestRegressor': RandomForestRegressor(),\n    'XGBRegressor': XGBRegressor()\n}\n\n#train ML Models\nfor name, model in ml_models.items():\n    model.fit(x_train, y_train)\n    results.append(ModelResult(name=name,cost=rmsle(y_validation, model.predict(x_validation)), model=model))"}, {'role': 'assistant', 'content': 'modelling'}]