Open Moelf opened 1 week ago
https://juliagaussianprocesses.github.io/AbstractGPs.jl/dev/examples/0-intro-1d/
mentions:
We create a finite dimensional projection at the inputs of the training dataset observed under Gaussian noise with variance noise_var=0.1
Is it the same thing as alpha in https://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html#sklearn.gaussian_process.GaussianProcessRegressor
alpha
which is the σ_n^2 in literature? https://gaussianprocess.org/gpml/chapters/RW.pdf#page=37
σ_n^2
Correct. I'd suggest taking a look at the docstrings for cov and FiniteGP.
cov
FiniteGP
https://juliagaussianprocesses.github.io/AbstractGPs.jl/dev/examples/0-intro-1d/
mentions:
Is it the same thing as
alpha
in https://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html#sklearn.gaussian_process.GaussianProcessRegressorwhich is the
σ_n^2
in literature? https://gaussianprocess.org/gpml/chapters/RW.pdf#page=37