Function check_X_y

sklearn/utils/validation.py:1183–1348

Input validation for standard estimators. Checks X and y for consistent length, enforces X to be 2D and y 1D. By default, X is checked to be non-empty and containing only finite values. Standard input checks are also applied to y, such as checking that y does not have np.nan or np.i

(
    X,
    y,
    accept_sparse=False,
    *,
    accept_large_sparse=True,
    dtype="numeric",
    order=None,
    copy=False,
    force_writeable=False,
    ensure_all_finite=True,
    ensure_2d=True,
    allow_nd=False,
    multi_output=False,
    ensure_min_samples=1,
    ensure_min_features=1,
    y_numeric=False,
    estimator=None,
)

def check_X_y(
    X,
    y,
    accept_sparse=False,
    *,
    accept_large_sparse=True,
    dtype="numeric",
    order=None,
    copy=False,
    force_writeable=False,
    ensure_all_finite=True,
    ensure_2d=True,
    allow_nd=False,
    multi_output=False,
    ensure_min_samples=1,
    ensure_min_features=1,
    y_numeric=False,
    estimator=None,
):
    """Input validation for standard estimators.

    Checks X and y for consistent length, enforces X to be 2D and y 1D. By
    default, X is checked to be non-empty and containing only finite values.
    Standard input checks are also applied to y, such as checking that y
    does not have np.nan or np.inf targets. For multi-label y, set
    multi_output=True to allow 2D and sparse y. If the dtype of X is
    object, attempt converting to float, raising on failure.

    Parameters
    ----------
    X : {ndarray, list, sparse matrix}
        Input data.

    y : {ndarray, list, sparse matrix}
        Labels.

    accept_sparse : str, bool or list of str, default=False
        String[s] representing allowed sparse matrix formats, such as 'csc',
        'csr', etc. If the input is sparse but not in the allowed format,
        it will be converted to the first listed format. True allows the input
        to be any format. False means that a sparse matrix input will
        raise an error.

    accept_large_sparse : bool, default=True
        If a CSR, CSC, COO or BSR sparse matrix is supplied and accepted by
        accept_sparse, accept_large_sparse will cause it to be accepted only
        if its indices are stored with a 32-bit dtype.

        .. versionadded:: 0.20

    dtype : 'numeric', type, list of type or None, default='numeric'
        Data type of result. If None, the dtype of the input is preserved.
        If "numeric", dtype is preserved unless array.dtype is object.
        If dtype is a list of types, conversion on the first type is only
        performed if the dtype of the input is not in the list.

    order : {'F', 'C'}, default=None
        Whether an array will be forced to be fortran or c-style. If