https://github.com/jungtaekkim/bayeso
Simple, but essential Bayesian optimization package
https://github.com/jungtaekkim/bayeso
bayesian-optimization hyperparameter-optimization machine-learning
Last synced: about 1 year ago
JSON representation
Simple, but essential Bayesian optimization package
- Host: GitHub
- URL: https://github.com/jungtaekkim/bayeso
- Owner: jungtaekkim
- License: mit
- Created: 2017-11-29T04:41:57.000Z (over 8 years ago)
- Default Branch: main
- Last Pushed: 2025-01-07T21:08:22.000Z (over 1 year ago)
- Last Synced: 2025-03-28T18:14:51.172Z (about 1 year ago)
- Topics: bayesian-optimization, hyperparameter-optimization, machine-learning
- Language: Python
- Homepage: https://bayeso.org
- Size: 5.38 MB
- Stars: 94
- Watchers: 5
- Forks: 9
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
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README
# BayesO: A Bayesian Optimization Framework in Python
[](https://doi.org/10.21105/joss.05320)
[](https://github.com/jungtaekkim/bayeso/actions/workflows/pytest.yml)
[](https://coveralls.io/github/jungtaekkim/bayeso?branch=main)
[](https://pypi.org/project/bayeso/)
[](https://opensource.org/licenses/MIT)
[](https://bayeso.readthedocs.io/en/main/?badge=main)
Simple, but essential Bayesian optimization package.
* [https://bayeso.org](https://bayeso.org)
* [Online documentation](https://bayeso.readthedocs.io)
## Installation
We recommend installing it with `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.
```shell
$ pip install bayeso
```
* Using source code (for developer installation)
To install `bayeso` from source code, command the following in the `bayeso` root.
```shell
pip install .
```
* Using source code (for editable development mode)
To use editable development mode, command the following in the `bayeso` root.
```shell
pip install -e .
```
If you want to install the packages required for optional features, development, and examples, you can simply add `[optional]`, `[dev]`, and `[examples]`.
For example, `pip install .[dev]` or `pip install -e .[dev]`.
* Uninstallation
If you would like to uninstall `bayeso`, command it.
```shell
$ pip uninstall bayeso
```
## Supported Python Version
We test our package in the following versions.
* Python 3.7
* Python 3.8
* Python 3.9
* Python 3.10
* Python 3.11
## Examples and Tests
We provide a [list of examples](EXAMPLES.md) and a [list of tests](TESTS.md).
## Citation
```
@article{KimJ2023joss,
author={Kim, Jungtaek and Choi, Seungjin},
title={{BayesO}: A {Bayesian} optimization framework in {Python}},
journal={Journal of Open Source Software},
volume={8},
number={90},
pages={5320},
year={2023}
}
```
## License
[MIT License](LICENSE)