LinearKernel

class baybe.kernels.basic.LinearKernel

Bases: BasicKernel

A linear kernel.

Public methods

__init__([variance_prior, ...])	Method generated by attrs for class LinearKernel.
from_dict(dictionary)	Create an object from its dictionary representation.
from_json(string)	Create an object from its JSON representation.
to_dict()	Create an object's dictionary representation.
to_factory()	Wrap the kernel in a baybe.surrogates.gaussian_process.kernel_factory.PlainKernelFactory.
to_gpytorch(*args, **kwargs)	Create the gpytorch representation of the kernel.
to_json()	Create an object's JSON representation.

Public attributes and properties

variance_prior	An optional prior on the kernel variance parameter.
variance_initial_value	An optional initial value for the kernel variance parameter.

__init__(variance_prior: Prior | None = None, variance_initial_value=None)

Method generated by attrs for class LinearKernel.

For details on the parameters, see Public attributes and properties.

classmethod from_dict(dictionary: dict)

Create an object from its dictionary representation.

Parameters:

dictionary (dict) – The dictionary representation.

Return type:

TypeVar(_T)

Returns:

The reconstructed object.

classmethod from_json(string: str)

Create an object from its JSON representation.

Parameters:

string (str) – The JSON representation of the object.

Return type:

TypeVar(_T)

Returns:

The reconstructed object.

to_dict()

Create an object’s dictionary representation.

Return type:

dict

to_factory()

Wrap the kernel in a baybe.surrogates.gaussian_process.kernel_factory.PlainKernelFactory.

Return type:

PlainKernelFactory

to_gpytorch(*args, **kwargs)

Create the gpytorch representation of the kernel.

to_json()

Create an object’s JSON representation.

Return type:

str

Returns:

The JSON representation as a string.

variance_initial_value: float | None

An optional initial value for the kernel variance parameter.

variance_prior: Prior | None

An optional prior on the kernel variance parameter.