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RoBO: a Robust Bayesian Optimization framework

License: BSD 3-Clause "New" or "Revised" License

Shell 0.23% Python 66.31% Jupyter Notebook 33.46%

robo's Introduction

RoBO - a Robust Bayesian Optimization framework.

Master Branch

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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,
}

robo's People

Contributors

aaronkl avatar numairmansur avatar antworteffekt avatar edublancas avatar amueller avatar jmetzen avatar keggensperger avatar infusion avatar sfalkner avatar frank-hutter avatar stokasto avatar

Watchers

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