ARC Code TI: Block-GP: Scalable Gaussian Process Regression
Description
Block GP is a Gaussian Process regression framework for multimodal data, that can be an order of magnitude more scalable than existing state-of-the-art nonlinear regression algorithms. The framework builds local Gaussian Processes on semantically meaningful partitions of the data and provides higher prediction accuracy than a single global model with very high confidence.
Resources
| Name |
Format |
Description |
Link |
|
45 |
BlockGP.tar.gz |
http://ti.arc.nasa.gov/m/opensource/downloads/BlockGP.tar.gz |
Tags
- regression
- data
- block-gp
- code-ti
- gaussian
- multimodal
- algorithm
- scalable