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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.

Version:1.0.1
Imports:R6,hash,DiceKriging,mlegp
Suggests:knitr,rmarkdown,spelling,testthat
Published:2024-10-16
DOI:10.32614/CRAN.package.GPTreeO
Author:Timo BraunORCID iD [aut, cre], Anders KvellestadORCID iD [aut], Riccardo De BinORCID iD [ctb]
Maintainer:Timo Braun <gptreeo.timo.braun at gmail.com>
License:MIT + fileLICENSE
NeedsCompilation:no
Language:en-US
Materials:NEWS
CRAN checks:GPTreeO results

Documentation:

Reference manual:GPTreeO.html ,GPTreeO.pdf
Vignettes:GPTreeO-Vignette (source,R code)

Downloads:

Package source: GPTreeO_1.0.1.tar.gz
Windows binaries: r-devel:GPTreeO_1.0.1.zip, r-release:GPTreeO_1.0.1.zip, r-oldrel:GPTreeO_1.0.1.zip
macOS binaries: r-release (arm64):GPTreeO_1.0.1.tgz, r-oldrel (arm64):GPTreeO_1.0.1.tgz, r-release (x86_64):GPTreeO_1.0.1.tgz, r-oldrel (x86_64):GPTreeO_1.0.1.tgz
Old sources: GPTreeO archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=GPTreeOto link to this page.


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