bulk_dice_binary_similarity#

skfp.distances.bulk_dice_binary_similarity(X: ndarray, Y: ndarray | None = None) → ndarray#

Bulk Dice similarity for binary matrices.

Computes the pairwise Dice similarity between binary matrices. If one array is passed, similarities are computed between its rows. For two arrays, similarities are between their respective rows, with i-th row and j-th column in output corresponding to i-th row from first array and j-th row from second array.

See also dice_binary_similarity().

Parameters:

  • X (ndarray) – First binary input array, of shape \(m \times m\)

  • Y (ndarray, default=None) – Second binary input array, of shape \(n \times n\). If not passed, similarities are computed between rows of X.

Returns:

similarities – Array with pairwise Dice similarity values. Shape is \(m \times n\) if two arrays are passed, or \(m \times m\) otherwise.

Return type:

ndarray

See also

dice_binary_similarity()

Dice similarity function for two vectors.

Examples

>>> from skfp.distances import bulk_dice_binary_similarity
>>> import numpy as np
>>> X = np.array([[1, 0, 1], [0, 0, 1]])
>>> Y = np.array([[1, 0, 1], [0, 1, 1]])
>>> sim = bulk_dice_binary_similarity(X, Y)
>>> sim
array([[1.        , 0.5       ],
       [0.66666667, 0.66666667]])