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

sklearn.metrics.pairwise.linear_kernel(X, Y=None, dense_output=True)

  Compute the linear kernel between X and Y.

  Read more in the User Guide.

  Parameters:
    X{array-like, sparse matrix} of shape (n_samples_X, n_features)

      A feature array.

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

      An optional second feature array. If `None`, uses `Y=X`.

    dense_output bool, default=True

      Whether to return dense output even when the input is sparse. If `False`, the output is sparse if both input arrays are sparse.

      New in version 0.20.

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

      The Gram matrix of the linear kernel, i.e. `X @ Y.T`.