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sklearn.metrics.pairwise.laplacian_kernel(X, Y=None, gamma=None)
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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)
sklearn.metrics.pairwise.laplacian_kernel()
2017-01-15 04:26:32
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