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scikit-learn 1.3.2
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# `sklearn.metrics.pairwise`.cosine_distances

sklearn.metrics.pairwise.cosine_distances(X, Y=None)

  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} of shape (n_samples_X, n_features)

      Matrix `X`.

    Y{array-like, sparse matrix} of shape (n_samples_Y, n_features), default=None

      Matrix `Y`.

  Returns:
    distance matrix ndarray of shape (n_samples_X, n_samples_Y)

      Returns the cosine distance between samples in X and Y.

  See also

  `cosine_similarity`

    Compute cosine similarity between samples in X and Y.

  `scipy.spatial.distance.cosine`

    Dense matrices only.