SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.
Description
skbel is a Python module for implementing the Bayesian Evidential Learning framework built on top of scikit-learn and is distributed under the 3-Clause BSD license.
Installation
Dependencies
skbel requires:
- Python (>= 3.7)
- Scikit-Learn (>= 0.24.1)
- NumPy (>= 1.14.6)
- SciPy (>= 1.1.0)
- joblib (>= 0.11)
Skbel plotting capabilities require Matplotlib (>= 2.2.2).
User installation
The easiest way to install skbel is using pip
pip install -U skbel
Development
We welcome new contributors of all experience levels.
Important links
- Official source code repo: https://github.com/robinthibaut/skbel/
- Download releases: https://pypi.org/project/skbel/
- Issue tracker: https://github.com/robinthibaut/skbel/issues
Source code
You can check the latest sources with the command:
git clone https://github.com/robinthibaut/skbel.git
Contributing
Contributors and feedback from users are welcome. Don't hesitate to submit an issue or a PR, or request a new feature.
Testing
After installation, you can launch the test suite from outside the source directory (you will need to have pytest
>= 5.0.1 installed):
pytest skbel
Help and Support
Documentation
- HTML documentation (latest release): https://skbel.readthedocs.io/en/latest/
Communication
- Github Discussions: https://github.com/robinthibaut/skbel/discussions
Files
robinthibaut/skbel-v1.1.0.zip
Files
(86.8 MB)
Name | Size | Download all |
---|---|---|
md5:fcaadd9b55c4024c828cfedc234fc603
|
86.8 MB | Preview Download |
Additional details
Related works
- Is supplement to
- https://github.com/robinthibaut/skbel/tree/v1.1.0 (URL)