GPTreeO
Dividing Local Gaussian Processes for Online Learning Regression
We implement and extend the Dividing Local Gaussian Process algorithm by Lederer et al. (2020) <doi:10.48550/arXiv.2006.09446>. Its main use case is in online learning where it is used to train a network of local GPs (referred to as tree) by cleverly partitioning the input space. In contrast to a single GP, 'GPTreeO' is able to deal with larger amounts of data. The package includes methods to create the tree and set its parameter, incorporating data points from a data stream as well as making joint predictions based on all relevant local GPs.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.1 |
rolling source/ R- | GPTreeO_1.0.1.tar.gz |
198.5 KiB |
1.0.1 |
rolling linux/jammy R-4.5 | GPTreeO_1.0.1.tar.gz |
478.0 KiB |
1.0.1 |
rolling linux/noble R-4.5 | GPTreeO_1.0.1.tar.gz |
477.9 KiB |
1.0.1 |
latest source/ R- | GPTreeO_1.0.1.tar.gz |
198.5 KiB |
1.0.1 |
latest linux/jammy R-4.5 | GPTreeO_1.0.1.tar.gz |
478.0 KiB |
1.0.1 |
latest linux/noble R-4.5 | GPTreeO_1.0.1.tar.gz |
477.9 KiB |
1.0.1 |
2026-04-23 source/ R- | GPTreeO_1.0.1.tar.gz |
198.5 KiB |
1.0.1 |
2026-04-09 windows/windows R-4.5 | GPTreeO_1.0.1.zip |
480.9 KiB |
1.0.1 |
2025-04-20 source/ R- | GPTreeO_1.0.1.tar.gz |
198.5 KiB |