shogun-toolbox/shogun — pull request #406 by puffin444 (2012-03-31 19:35:04+00:00)
Title: Gaussian Process Regression for GSoC

Here is a very basic implementation of a Gaussian Process Regression class with a small example in Shogun. Right now it only returns mean predictions, but it would be very straightforward to add a function which returns the covariance. I do have a few questions/comments, however:

1. Does this design make sense? Because GPs infer in function space, not weight space, it inherits directly
from the Machine class instead of KernelMachine. Currently the apply function returns mean predictions.

2. Does the formatting/commenting fit Shogun's standards?

3. I found no memory leaks using Valgrind on the test example. Please let me know though if you find a huge bug or inaccuracy in computation.

4. Right now its a straightforward implementation; I hope to eventually find ways to optimize performance.

Thank You For Your Consideration and Time,

Puffin444