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A fully Bayesian implementation of sequential model-based optimization

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Bayes-skopt Documentation Status

A fully Bayesian implementation of sequential model-based optimization


  • 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.


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+

Another option is to clone the repository and install Bayes-skopt using:

poetry install


This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

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