Simple, but essential Bayesian optimization package

Related tags

Deep Learningmachine-learninghyperparameter-optimizationbayesian-optimization
Overview

BayesO: A Bayesian optimization framework in Python

Build Status Coverage Status PyPI - Python Version License: MIT Documentation Status

Simple, but essential Bayesian optimization package.

Installation

We recommend it should be installed in virtualenv. You can choose one of three installation options.

  • Using PyPI repository (for user installation)

To install the released version in PyPI repository, command it.

$ pip install bayeso
  • Using source code (for developer installation)

To install bayeso from source code, command

$ pip install .

in the bayeso root.

  • Using source code (for editable development mode)

To use editable development mode, command

$ pip install -r requirements.txt
$ python setup.py develop

in the bayeso root.

  • Uninstallation

If you would like to uninstall bayeso, command it.

$ pip uninstall bayeso

Required Packages

Mandatory pacakges are inlcuded in requirements.txt. The following requirements files include the package list, the purpose of which is described as follows.

  • requirements-optional.txt: It is an optional package list, but it needs to be installed to execute some features of bayeso.
  • requirements-dev.txt: It is for developing the bayeso package.
  • requirements-examples.txt: It needs to be installed to execute the examples included in the bayeso repository.

Supported Python Version

We test our package in the following versions.

  • Python 3.6
  • Python 3.7
  • Python 3.8

Contributor

Citation

@misc{KimJ2017bayeso,
    author={Kim, Jungtaek and Choi, Seungjin},
    title={{BayesO}: A {Bayesian} optimization framework in {Python}},
    howpublished={\url{http://bayeso.org}},
    year={2017}
}

Contact

License

MIT License

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Owner
Jungtaek Kim
Jungtaek Kim
GitHub Repository http://bayeso.org
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