A simple Python/Cython module implementing a domain specific language to manage
configuration spaces for algorithm configuration and hyperparameter optimization tasks.
Distributed under BSD 3-clause, see LICENSE except all files in the directory
ConfigSpace.nx, which are copied from the networkx package and licensed
under a BSD license.
The documentation can be found at https://automl.github.io/ConfigSpace/main/. Further examples can be found in the SMAC documentation.
from ConfigSpace import ConfigurationSpace
cs = ConfigurationSpace(
name="myspace",
space={
"a": (0.1, 1.5), # UniformFloat
"b": (2, 10), # UniformInt
"c": ["mouse", "cat", "dog"], # Categorical
},
)
configs = cs.sample_configuration(2)
@article{
title = {BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters},
author = {M. Lindauer and K. Eggensperger and M. Feurer and A. Biedenkapp and J. Marben and P. Müller and F. Hutter},
journal = {arXiv:1908.06756 {[cs.LG]}},
date = {2019},
}