Euclidean Kernels
Euclidean Kernel Class
The EuclideanKernel
class is the parent class for all Euclidean kernels. It is imported using the following
command:
>>> from UQpy.utilities.kernels.baseclass.EuclideanKernel import EuclideanKernel
Gaussian Kernel
The Gaussian kernel is defined by:
The GaussianKernel
class is imported using the following command:
>>> from UQpy.utilities.kernels.GaussianKernel import GaussianKernel
One can use the following to instantiate the GaussianKernel
class.
Methods
- class GaussianKernel(kernel_parameter=1.0)[source]
- Parameters:
epsilon – Scale parameter of the Gaussian kernel
- optimize_parameters(data, tolerance, n_nearest_neighbors, n_cutoff_samples, random_state=None)[source]
- Parameters:
data (
ndarray
) – Set of data points.tolerance (
float
) – Tolerance below which the Gaussian kernel is assumed to be zero.n_nearest_neighbors (
int
) – Number of neighbors to use for cut-off estimation.n_cutoff_samples (
int
) – Number of samples to use for cut-off estimation.random_state (
Union
[None
,int
,RandomState
]) – Random seed used to initialize the pseudo-random number generator. If anint
is provided, this sets the seed for an object ofnumpy.random.RandomState
. Otherwise, the object itself can be passed directly.
Attributes
- GaussianKernel.kernel_matrix