yamle.methods.gp module

class yamle.methods.gp.GPMethod(prior_mean='constant', prior_covariance='rbf', num_inducing_points=100, num_latent=3, *args, **kwargs)

Bases: BaseMethod

This class implements the Gaussian Process (GP) method.

Parameters:

• prior_mean (str) – The prior mean function.

• prior_covariance (str) – The prior covariance function.

• num_inducing_points (int) – The inducing points.

• num_latent (int) – The latent dimension.

tasks = ['classification', 'regression']

state_dict()

Get the state dictionary of the model.

Return type:

Dict[str, Any]

load_state_dict(state_dict)

Load the state dictionary of the model.

Return type:

None

get_parameters(recurse=True)

This method is used to get the parameters of the model.

Return type:

List[Parameter]

static add_specific_args(parent_parser)

This method is used to add method specific arguments to the parent parser.

Return type:

ArgumentParser