[{'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:top_10_map = OrderedDict([\n('BROADWAY', broadway),\n('NORTHERN BOULEVARD', northern),\n('ATLANTIC AVENUE', atlantic_avenue),\n('BEDFORD AVENUE', bedford),\n('JAMAICA AVENUE', jamaica),\n('UNION TURNPIKE', union),\n('AMBOY ROAD', amboy),\n('KILL ROAD', kill),\n('NOSTRAND AVENUE', nostrand),\n('LIBERTY AVENUE', liberty),\n])\nfeatures = []\nfor (street, dist) in zip(top_10_map.keys(), distances):\ngeom = geojson.LineString(top_10_map[street].tolist())\nfeatures.append(geojson.Feature(geometry=geom, properties={'name': street, 'distance': dist}))\nwith open('streets.geojson', 'w') as file:\nfile.write(geojson.dumps(geojson.FeatureCollection(features), sort_keys=True))"}, {'role': 'assistant', 'content': "['prediction', 'save_results']"}]