sklearn.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 : array An array with shape (n_samples_X, n_samples_Y). |
See also
sklearn.metrics.pairwise.cosine_similarity, scipy.spatial.distance.cosine
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Licensed under the 3-clause BSD License.
http://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_distances.html