openml.evaluations.list_evaluations_setups(function: str, offset: Optional[int] = None, size: Optional[int] = None, tasks: Optional[List] = None, setups: Optional[List] = None, flows: Optional[List] = None, runs: Optional[List] = None, uploaders: Optional[List] = None, tag: Optional[str] = None, per_fold: Optional[bool] = None, sort_order: Optional[str] = None, output_format: str = 'dataframe', parameters_in_separate_columns: bool = False) Union[Dict, pandas.core.frame.DataFrame]

List all run-evaluation pairs matching all of the given filters and their hyperparameter settings.


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

dict or dataframe with hyperparameter settings as a list of tuples.