-
sklearn.metrics.pairwise.rbf_kernel(X, Y=None, gamma=None)
[source] -
Compute the rbf (gaussian) kernel between X and Y:
1K(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 : 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.rbf_kernel()

2025-01-10 15:47:30
Please login to continue.