bulk_ct4_binary_similarity#
- skfp.distances.bulk_ct4_binary_similarity(X: ndarray, Y: ndarray | None = None) ndarray #
Bulk Consonni–Todeschini 4 similarity for binary matrices.
Computes the pairwise Consonni–Todeschini 4 (CT4) 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
ct4_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 Consonni–Todeschini similarity values. Shape is \(m \times n\) if two arrays are passed, or \(m \times m\) otherwise.
- Return type:
ndarray
See also
ct4_binary_similarity()
Consonni–Todeschini similarity function for two vectors.
Examples
>>> from skfp.distances import bulk_ct4_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_ct4_binary_similarity(X, Y) >>> sim array([[1. , 0.5 ], [0.63092975, 0.63092975]])