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
- Xndarray of shape (n_samples_X, n_features)
- Yndarray of shape (n_samples_Y, n_features), default=None
If
None, usesY=X.- gammafloat, default=None
If None, defaults to 1.0 / n_features.
- Returns
- kernel_matrixndarray of shape (n_samples_X, n_samples_Y)