Illustration of Gaussian process classification on the XOR dataset

This example illustrates GPC on XOR data. Compared are a stationary, isotropic kernel (RBF) and a non-stationary kernel

2017-01-15 04:22:52
Gaussian process regression with noise-level estimation

This example illustrates that GPR with a sum-kernel including a WhiteKernel can estimate the noise level of data. An illustration

2017-01-15 04:22:27
Comparison of kernel ridge and Gaussian process regression

Both kernel ridge regression (KRR) and Gaussian process regression (GPR) learn a target function by employing internally the ?kernel

2017-01-15 04:20:50
Probabilistic predictions with Gaussian process classification

This example illustrates the predicted probability of GPC for an RBF kernel with different choices of the hyperparameters

2017-01-15 04:25:14
Iso-probability lines for Gaussian Processes classification

A two-dimensional classification example showing iso-probability lines for the predicted probabilities.

2017-01-15 04:22:55
Illustration of prior and posterior Gaussian process for different kernels

This example illustrates the prior and posterior of a GPR with different kernels. Mean, standard deviation, and 10

2017-01-15 04:22:52
Gaussian process classification on iris dataset

This example illustrates the predicted probability of GPC for an isotropic and anisotropic RBF kernel on a two-dimensional version for the

2017-01-15 04:22:26
Gaussian Processes regression

A simple one-dimensional regression example computed in two different ways: A noise-free case

2017-01-15 04:22:28
Gaussian process regression on Mauna Loa CO2 data.

This example is based on Section 5.4.3 of ?Gaussian Processes for Machine Learning? [RW2006]. It illustrates an example of complex kernel

2017-01-15 04:22:26