Implementing Gaussian Process Regession in Shogun
Jacob Walker
Abstract
This project focuses on implementing Gaussian Process Regression with hyperparameter learning in Shogun. The goal is to make the implementation easily extendable and able to handle large datasets through sparse approximation.
Code samples
| File name | Size | Date submitted |
|---|---|---|
| Jacob_Walker.tar.gz | 163.6 KB | September 10 2012 04:46 UTC |
