split

openml.tasks.split

OpenMLSplit

OpenMLSplit(name: int | str, description: str, split: dict[int, dict[int, dict[int, tuple[ndarray, ndarray]]]])

OpenML Split object.

This class manages train-test splits for a dataset across multiple repetitions, folds, and samples.

Parameters

name : int or str The name or ID of the split. description : str A description of the split. split : dict A dictionary containing the splits organized by repetition, fold, and sample.

Source code in openml/tasks/split.py

def __init__(
    self,
    name: int | str,
    description: str,
    split: dict[int, dict[int, dict[int, tuple[np.ndarray, np.ndarray]]]],
):
    self.description = description
    self.name = name
    self.split: dict[int, dict[int, dict[int, tuple[np.ndarray, np.ndarray]]]] = {}

    # Add splits according to repetition
    for repetition in split:
        _rep = int(repetition)
        self.split[_rep] = OrderedDict()
        for fold in split[_rep]:
            self.split[_rep][fold] = OrderedDict()
            for sample in split[_rep][fold]:
                self.split[_rep][fold][sample] = split[_rep][fold][sample]

    self.repeats = len(self.split)

    # TODO(eddiebergman): Better error message
    if any(len(self.split[0]) != len(self.split[i]) for i in range(self.repeats)):
        raise ValueError("")

    self.folds = len(self.split[0])
    self.samples = len(self.split[0][0])

get

get(repeat: int = 0, fold: int = 0, sample: int = 0) -> tuple[ndarray, ndarray]

Returns the specified data split from the CrossValidationSplit object.

Parameters

repeat : int Index of the repeat to retrieve. fold : int Index of the fold to retrieve. sample : int Index of the sample to retrieve.

Returns

numpy.ndarray The data split for the specified repeat, fold, and sample.

Raises

ValueError If the specified repeat, fold, or sample is not known.

Source code in openml/tasks/split.py

def get(self, repeat: int = 0, fold: int = 0, sample: int = 0) -> tuple[np.ndarray, np.ndarray]:
    """Returns the specified data split from the CrossValidationSplit object.

    Parameters
    ----------
    repeat : int
        Index of the repeat to retrieve.
    fold : int
        Index of the fold to retrieve.
    sample : int
        Index of the sample to retrieve.

    Returns
    -------
    numpy.ndarray
        The data split for the specified repeat, fold, and sample.

    Raises
    ------
    ValueError
        If the specified repeat, fold, or sample is not known.
    """
    if repeat not in self.split:
        raise ValueError(f"Repeat {repeat!s} not known")
    if fold not in self.split[repeat]:
        raise ValueError(f"Fold {fold!s} not known")
    if sample not in self.split[repeat][fold]:
        raise ValueError(f"Sample {sample!s} not known")
    return self.split[repeat][fold][sample]

Split

Bases: NamedTuple

A single split of a dataset.