openml.evaluations.list_evaluations¶
- openml.evaluations.list_evaluations(function: str, offset: int | None = None, size: int | None = 10000, tasks: List[str | int] | None = None, setups: List[str | int] | None = None, flows: List[str | int] | None = None, runs: List[str | int] | None = None, uploaders: List[str | int] | None = None, tag: str | None = None, study: int | None = None, per_fold: bool | None = None, sort_order: str | None = None, output_format: str = 'object') Dict | DataFrame¶
List all run-evaluation pairs matching all of the given filters. (Supports large amount of results)
- Parameters:
- functionstr
the evaluation function. e.g., predictive_accuracy
- offsetint, optional
the number of runs to skip, starting from the first
- sizeint, default 10000
The maximum number of runs to show. If set to
None, it returns all the results.- taskslist[int,str], optional
the list of task IDs
- setups: list[int,str], optional
the list of setup IDs
- flowslist[int,str], optional
the list of flow IDs
- runs :list[int,str], optional
the list of run IDs
- uploaderslist[int,str], optional
the list of uploader IDs
- tagstr, optional
filter evaluation based on given tag
- studyint, optional
- per_foldbool, optional
- sort_orderstr, optional
order of sorting evaluations, ascending (“asc”) or descending (“desc”)
- output_format: str, optional (default=’object’)
The parameter decides the format of the output. - If ‘object’ the output is a dict of OpenMLEvaluation objects - If ‘dict’ the output is a dict of dict - If ‘dataframe’ the output is a pandas DataFrame
- Returns:
- dict or dataframe