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scikit-learn 1.3.2
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# `sklearn.utils.validation`.check_symmetric

sklearn.utils.validation.check_symmetric(array, *, tol=1e-10, raise_warning=True, raise_exception=False)

  Make sure that array is 2D, square and symmetric.

  If the array is not symmetric, then a symmetrized version is returned. Optionally, a warning or exception is raised if the matrix is not symmetric.

  Parameters:
    array{ndarray, sparse matrix}

      Input object to check / convert. Must be two-dimensional and square, otherwise a ValueError will be raised.

    tol float, default=1e-10

      Absolute tolerance for equivalence of arrays. Default = 1E-10.

    raise_warning bool, default=True

      If True then raise a warning if conversion is required.

    raise_exception bool, default=False

      If True then raise an exception if array is not symmetric.

  Returns:
    array_sym{ndarray, sparse matrix}

      Symmetrized version of the input array, i.e. the average of array and array.transpose(). If sparse, then duplicate entries are first summed and zeros are eliminated.