[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': "Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:from sklearn import tree\nclf = tree.tree.DecisionTreeRegressor(max_depth=4,criterion='mse',min_samples_leaf=800)\nclf = clf.fit(train['hour'].reshape(-1,1),np.ravel(train['count']))\nimport graphviz \ndot_data = tree.export_graphviz(clf, out_file=None,feature_names=['hour'],  \n                                filled=True, rounded=True,  \n                                special_characters=True,) \ngraph = graphviz.Source(dot_data) \ngraph\n#dot_data = tree.export_graphviz(clf, out_file=None,feature_names=train[['hour']].columns.values,class_names=train[['count']].columns.values) \n#graph = graphviz.Source(dot_data)  \n#graph \n"}, {'role': 'assistant', 'content': "['modelling']"}]