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Decision brief
RoBO is a Python framework for robust Bayesian optimization using Gaussian processes and random forests.
Good fit when
- For tasks requiring robust handling of noisy data in Bayesian Optimization
- When needing integration with libraries like [george] and [pyrfr]
Avoid when
- Avoid if your project strictly requires open-source licenses other than BSD-3-Clause
- Not suitable for users not comfortable installing external dependencies manually
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (2653d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- 15 low (15 low)
- As of 1mo
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Install
pip install RoBOSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
RoBO is a Python-based framework for conducting robust Bayesian Optimization, making use of Gaussian processes and random forests libraries for optimization tasks.
Capability facts
- Languages
- python
Source: github.language · Aug 4, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 4, 2026)
python setup.py installSource link
Tags
README
RoBO - a Robust Bayesian Optimization framework.
Master Branch
Installation
RoBO uses the Gaussian processes library george and the random forests library pyrfr. In order to use these libraries make sure that libeigen and swig are installed:
sudo apt-get install libeigen3-dev swig
Download RoBO and then change into the new directory:
git clone https://github.com/automl/RoBO
cd RoBO/
Install the required dependencies.
for req in $(cat requirements.txt); do pip install $req; done
Finally install RoBO by:
python setup.py install
Documentation
You can find the documentation for RoBO here http://automl.github.io/RoBO/
Citing RoBO
To cite RoBO please reference our BayesOpt paper:
@INPROCEEDINGS{klein-bayesopt17,
author = {A. Klein and S. Falkner and N. Mansur and F. Hutter},
title = {RoBO: A Flexible and Robust Bayesian Optimization Framework in Python},
booktitle = {NIPS 2017 Bayesian Optimization Workshop},
year = {2017},
month = dec,
}
For agents
This page has a .md twin and JSON over the API.