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GPTreeO

Dividing Local Gaussian Processes for Online Learning Regression

v1.0.1 · Oct 16, 2024 · MIT + file LICENSE

Description

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.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies R6 hash DiceKriging mlegp GPTreeO

Version History

new 1.0.1 Mar 9, 2026