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