sklearn.metrics.pairwise.laplacian_kernel

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_features
Returns:	kernel_matrix : array of shape (n_samples_X, n_samples_Y)