evaluation

openml.evaluations.evaluation

OpenMLEvaluation

OpenMLEvaluation(run_id: int, task_id: int, setup_id: int, flow_id: int, flow_name: str, data_id: int, data_name: str, function: str, upload_time: str, uploader: int, uploader_name: str, value: float | None, values: list[float] | None, array_data: str | None = None)

Contains all meta-information about a run / evaluation combination, according to the evaluation/list function

Parameters

run_id : int Refers to the run. task_id : int Refers to the task. setup_id : int Refers to the setup. flow_id : int Refers to the flow. flow_name : str Name of the referred flow. data_id : int Refers to the dataset. data_name : str The name of the dataset. function : str The evaluation metric of this item (e.g., accuracy). upload_time : str The time of evaluation. uploader: int Uploader ID (user ID) upload_name : str Name of the uploader of this evaluation value : float The value (score) of this evaluation. values : List[float] The values (scores) per repeat and fold (if requested) array_data : str list of information per class. (e.g., in case of precision, auroc, recall)

Source code in openml/evaluations/evaluation.py

def __init__(  # noqa: PLR0913
    self,
    run_id: int,
    task_id: int,
    setup_id: int,
    flow_id: int,
    flow_name: str,
    data_id: int,
    data_name: str,
    function: str,
    upload_time: str,
    uploader: int,
    uploader_name: str,
    value: float | None,
    values: list[float] | None,
    array_data: str | None = None,
):
    self.run_id = run_id
    self.task_id = task_id
    self.setup_id = setup_id
    self.flow_id = flow_id
    self.flow_name = flow_name
    self.data_id = data_id
    self.data_name = data_name
    self.function = function
    self.upload_time = upload_time
    self.uploader = uploader
    self.uploader_name = uploader_name
    self.value = value
    self.values = values
    self.array_data = array_data