GPTreeO
1.0.1Dividing Local Gaussian Processes for Online Learning Regression
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 17%
- References docs
- 0%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 1.0.1Latest
- 1.0.02024-09-23
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2024-09-23
- Total releases
- 2 / 2 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 200 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
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