[{'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:importances = forest.feature_importances_\nstd = np.std([tree.feature_importances_ for tree in forest.estimators_],\naxis=0)\nindices = np.argsort(importances)[::-1]\nprint("Feature ranking:")\nfor f in range(train.shape[1]):\nprint("%d. feature %d (%f)" % (f + 1, indices[f], importances[indices[f]]))\nplt.figure()\nplt.title("Feature importances")\nplt.bar(range(train.shape[1]), importances[indices],\ncolor="r", yerr=std[indices], align="center")\nplt.xticks(range(train.shape[1]), indices)\nplt.xlim([-1, train.shape[1]])\nplt.show()'}, {'role': 'assistant', 'content': "['result_visualization']"}]