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.
- Version1.0.1
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Languageen-US
- Last release10/16/2024
Documentation
Team
Timo Braun
Anders Kvellestad
Riccardo De Bin
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- Imports4 packages
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