A fully Bayesian implementation of sequential model-based optimization
Project description
Bayes-skopt
A fully Bayesian implementation of sequential model-based optimization
Free software: Apache Software License 2.0
Documentation: https://bayes-skopt.readthedocs.io.
Built on top of the excellent Scikit-Optimize (skopt).
Features
A fully Bayesian variant of the GaussianProcessRegressor.
State of the art information-theoretic acquisition functions, such as the Max-value entropy search or Predictive variance reduction search, for even faster convergence in simple regret.
Familiar Optimizer interface known from Scikit-Optimize.
Installation
To install the latest stable release it is best to install the version on PyPI:
pip install bask
The latest development version of Bayes-skopt can be installed from Github as follows:
pip install git+https://github.com/kiudee/bayes-skopt
Another option is to clone the repository and install Bayes-skopt using:
python setup.py install
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
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