GaussianProcessRegressor

GaussianProcessRegressor

A model type for constructing a Gaussian process regressor, based on MLJScikitLearnInterface.jl, and implementing the MLJ model interface.

From MLJ, the type can be imported using

GaussianProcessRegressor = @load GaussianProcessRegressor pkg=MLJScikitLearnInterface

Do model = GaussianProcessRegressor() to construct an instance with default hyper-parameters. Provide keyword arguments to override hyper-parameter defaults, as in GaussianProcessRegressor(kernel=...).

Hyper-parameters

• kernel = nothing
• alpha = 1.0e-10
• optimizer = fmin_l_bfgs_b
• n_restarts_optimizer = 0
• normalize_y = false
• copy_X_train = true
• random_state = nothing