[{'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:b"#Novo modelo usando colunas roling\\n# instanciar o modelo\\nrf3 = RandomForestRegressor(random_state=42,n_jobs=-1, n_estimators=200, min_samples_leaf=5)\\n#n_jobs nr de job que rodam e paralalo para dar o fit. -1  #para usar todos os processadores\\n#n_estimator  - nro de arvores. o defalt  10 mas mudar para 100 na proxima verso 0.22\\n\\n#treinar o modelo com os dados de treino\\n\\nrf3.fit(train[feats], train[\'count\'])\\n\\n#Previses com os dados de validao\\npreds3 = rf3.predict(valid[feats])\\n\\n# Aplicar mtrica sobre os dados de validao\\n\\nmean_squared_error(valid[\'count\'], preds3)**(1/2)"'}, {'role': 'assistant', 'content': 'modelling'}]