TrainableKernel¶

class TrainableKernel(*, training_parameters=None, **kwargs)[소스]¶

기반 클래스: BaseKernel, ABC

An abstract definition of the ability to train kernel via specifying training parameters.

매개변수:

training_parameters (ParameterVector | Sequence[Parameter] | None) – a sequence of training parameters.
**kwargs – Additional parameters may be used by the super class.

Attributes

`enforce_psd`	Returns `True` if the kernel matrix is required to project to the closest positive semidefinite matrix.
`feature_map`	Returns the feature map of this kernel.
`num_features`	Returns the number of features in this kernel.
`num_training_parameters`	Returns the number of training parameters.
`parameter_values`	Returns numerical values assigned to the training parameters as a numpy array.
`training_parameters`	Returns the vector of training parameters.

Methods

`assign_training_parameters`(parameter_values)	Fix the training parameters to numerical values.
`evaluate`(x_vec[, y_vec])	Construct kernel matrix for given data.