{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"ds-1000","formal_name":"DS-1000","introduction":"DS-1000 builds 1,000 data-science problems from real StackOverflow questions across seven libraries including NumPy, Pandas and Matplotlib. The problems are perturbed so that recalling the original answer does not solve them.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://ds1000-code-gen.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"861fe9ba-d62a-5a01-aa12-b4e699c8937f","task_key":"default--test--929","task_revision_id":"1","upstream_id":"929","short_description":"I have set up a GridSearchCV and have a set of parameters, with I will find the…","config":"default","split":"test","body":"{\"library\":\"Sklearn\",\"prompt\":\"Problem:\\n\\nI have set up a GridSearchCV and have a set of parameters, with I will find the best combination of parameters. My GridSearch consists of 12 candidate models total.\\n\\nHowever, I am also interested in seeing the accuracy score of all of the 12, not just the best score, as I can clearly see by using the .best_score_ method. I am curious about opening up the black box that GridSearch sometimes feels like.\\n\\nI see a scoring= argument to GridSearch, but I can't see any way to print out scores. Actually, I want the full results of GridSearchCV besides getting the score, in pandas dataframe sorted by mean_fit_time.\\n\\nAny advice is appreciated. Thanks in advance.\\n\\n\\nA:\\n\\n<code>\\nimport numpy as np\\nimport pandas as pd\\nfrom sklearn.model_selection import GridSearchCV\\nGridSearch_fitted = load_data()\\nassert type(GridSearch_fitted) == sklearn.model_selection._search.GridSearchCV\\n</code>\\nfull_results = ... # put solution in this variable\\nBEGIN SOLUTION\\n<code>\\n\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://ds1000-code-gen.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}