sklearn.metrics.pairwise.laplacian_kernel(X, Y=None, gamma=None) [source]
Compute the laplacian kernel between X and Y.
The laplacian kernel is defined as:
K(x, y) = exp(-gamma ||x-y||_1)
for each pair of rows x in X and y in Y. Read more in the User Guide.
New in version 0.17.
| Parameters: |
X : array of shape (n_samples_X, n_features) Y : array of shape (n_samples_Y, n_features) gamma : float, default None If None, defaults to 1.0 / n_samples_X |
|---|---|
| Returns: |
kernel_matrix : array of shape (n_samples_X, n_samples_Y) |
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Licensed under the 3-clause BSD License.
http://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.laplacian_kernel.html