mars.learn.metrics.pairwise.rbf_kernel#
- mars.learn.metrics.pairwise.rbf_kernel(X, Y=None, gamma=None)[source]#
Compute the rbf (gaussian) kernel between X and Y:
K(x, y) = exp(-gamma ||x-y||^2)
for each pair of rows x in X and y in Y.
Read more in the User Guide.
- Parameters
X (tensor of shape (n_samples_X, n_features)) –
Y (tensor of shape (n_samples_Y, n_features)) –
gamma (float, default None) – If None, defaults to 1.0 / n_features
- Returns
kernel_matrix
- Return type
tensor of shape (n_samples_X, n_samples_Y)