[{'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:#Regression on everything\nfrom sklearn.ensemble import RandomForestRegressor\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nsns.set_context("notebook", font_scale=1.1)\nsns.set_style("ticks")\n\nimport numpy\nxTrain = pd.DataFrame({\'OpenDays\':trainData[\'OpenDays\'].apply(numpy.log),\n                      \'Big Cities\':trainData[\'Big Cities\'], \'Other\':trainData[\'Other\'],\n                      \'P2\':trainData[\'P2\'], \'P8\':trainData[\'P8\'], \'P22\':trainData[\'P22\'],\n                      \'P24\':trainData[\'P24\'], \'P28\':trainData[\'P28\'], \'P26\':trainData[\'P26\']})\n#xTrain = trainData.drop([\'revenue\'], axis=1)\n#xTrain[\'OpenDays\'] = xTrain[\'OpenDays\'].apply(numpy.log)\nyTrain = trainData[\'revenue\'].apply(numpy.log)\nxTest = pd.DataFrame({\'OpenDays\':testData[\'OpenDays\'].apply(numpy.log),\n                      \'Big Cities\':testData[\'Big Cities\'], \'Other\':testData[\'Other\'],\n                     \'P2\':testData[\'P2\'], \'P8\':testData[\'P8\'], \'P22\':testData[\'P22\'],\n                      \'P24\':testData[\'P24\'], \'P28\':testData[\'P28\'], \'P26\':testData[\'P26\']})\n\nfrom sklearn import linear_model\n\ncls = RandomForestRegressor(n_estimators=150)\ncls.fit(xTrain, yTrain)\npred = cls.predict(xTest)\npred = numpy.exp(pred)\ncls.score(xTrain, yTrain)\''}, {'role': 'assistant', 'content': 'modelling'}]