mars.learn.metrics.pairwise.cosine_distances#
- mars.learn.metrics.pairwise.cosine_distances(X, Y=None)[source]#
Compute cosine distance between samples in X and Y.
Cosine distance is defined as 1.0 minus the cosine similarity.
Read more in the User Guide.
- Parameters
X (array_like, sparse matrix) – with shape (n_samples_X, n_features).
Y (array_like, sparse matrix (optional)) – with shape (n_samples_Y, n_features).
- Returns
distance matrix – A tensor with shape (n_samples_X, n_samples_Y).
- Return type
Tensor
See also
mars.learn.metrics.pairwise.cosine_similarity
mars.tensor.spatial.distance.cosine
dense matrices only