openml.evaluations.list_evaluations_setups¶
- openml.evaluations.list_evaluations_setups(function: str, offset: int | None = None, size: int | None = None, tasks: list | None = None, setups: list | None = None, flows: list | None = None, runs: list | None = None, uploaders: list | None = None, tag: str | None = None, per_fold: bool | None = None, sort_order: str | None = None, output_format: str = 'dataframe', parameters_in_separate_columns: bool = False) dict | pd.DataFrame¶
List all run-evaluation pairs matching all of the given filters and their hyperparameter settings.
- Parameters:
- functionstr
the evaluation function. e.g., predictive_accuracy
- offsetint, optional
the number of runs to skip, starting from the first
- sizeint, optional
the maximum number of runs to show
- taskslist[int], optional
the list of task IDs
- setups: list[int], optional
the list of setup IDs
- flowslist[int], optional
the list of flow IDs
- runslist[int], optional
the list of run IDs
- uploaderslist[int], optional
the list of uploader IDs
- tagstr, optional
filter evaluation based on given tag
- per_foldbool, optional
- sort_orderstr, optional
order of sorting evaluations, ascending (“asc”) or descending (“desc”)
- output_format: str, optional (default=’dataframe’)
The parameter decides the format of the output. - If ‘dict’ the output is a dict of dict - If ‘dataframe’ the output is a pandas DataFrame
- parameters_in_separate_columns: bool, optional (default= False)
Returns hyperparameters in separate columns if set to True. Valid only for a single flow
- Returns:
- dict or dataframe with hyperparameter settings as a list of tuples.