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)