[{'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:name1 = ['Residual for casual without polynomial features'] *1633\nname2 = ['Residual for casual with polynomial features'] *1633\nname3 = ['Residual for registered without polynomial features'] *1633\nname4 = ['Residual for registered with polynomial features'] *1633\ndic = {'Lin': 'Output Predicted using linear model',\n       'Lin_poly': 'Output Predicted using polynomial features',\n       'RF' : 'Output Predicted using RandomForest Model', \n       'XG': 'Output Predicted using XGBoost Model',\n       'Resid':'Deviation from predicted','Output':'Expected Output',\n       'Resid_poly':'Deviation from predicted','Resid_rf':'Deviation from predicted',\n       'Output':'Expected Output','Resid_xg':'Deviation from predicted'}\nfig1 = px.scatter(data_frame = x1_final,x = 'Linear', y = 'Resid',hover_data = ['Output'],\n                  labels = dic,hover_name = name3,color_discrete_sequence = ['red'])\nfig2 = px.scatter(data_frame = x1_final,x = 'Lin_poly', y = 'Resid_poly',\n                  hover_data = ['Output'],labels = dic,hover_name = name4,\n                  color_discrete_sequence = ['blue'])\nfig3 = px.scatter(data_frame = x2_final,x = 'Linear', y = 'Resid',hover_data = ['Output'],\n                  labels = dic,hover_name = name1,color_discrete_sequence = ['darkgreen'])\nfig4 = px.scatter(data_frame = x2_final,x = 'Lin_poly', y = 'Resid_poly',\n                  hover_data = ['Output'],labels = dic,hover_name = name2,\n                  color_discrete_sequence = ['gold'])\n\ntrace1 = fig1['data'][0]\ntrace2 = fig2['data'][0]\ntrace3 = fig3['data'][0]\ntrace4 = fig4['data'][0]\n\n\nfig = make_subplots(rows=2, cols=2,horizontal_spacing =0.1,vertical_spacing  = 0.2,\n                    row_titles = ['Linear Model','Polynomial Model'],\n                    column_titles = ['Casual','Registered'],\n                    x_title = 'Residual plots for Registered and Casual under different models (Hover for more details)')\n\nfig.add_trace(trace3, row=1, col=1)\nfig.add_trace(trace4, row=2, col=1)\nfig.add_trace(trace1, row=1, col=2)\nfig.add_trace(trace2, row=2, col=2)\n\nfig.show()"}, {'role': 'assistant', 'content': 'result_visualization'}]