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https://github.com/bambinos/kulprit

Kullback-Leibler projections for Bayesian model selection in Python

https://github.com/bambinos/kulprit

Science Score: 39.0%

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    CITATION.cff file
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    Found codemeta.json file
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    Found .zenodo.json file
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    DOI references
    Found 5 DOI reference(s) in README
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    Scientific vocabulary similarity
    Low similarity (21.1%) to scientific vocabulary

Keywords

bayesian-inference kullback-leibler-divergence model-selection
Last synced: 6 months ago · JSON representation

Repository

Kullback-Leibler projections for Bayesian model selection in Python

Basic Info
Statistics
  • Stars: 38
  • Watchers: 5
  • Forks: 5
  • Open Issues: 5
  • Releases: 5
Topics
bayesian-inference kullback-leibler-divergence model-selection
Created about 4 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog Contributing Code of conduct

README.md

Kullback-Leibler projections for Bayesian model selection in Python.

PyPi version Build Status codecov Code style: black

Overview

Kulprit (Pronounced: kuːl.prɪt) is a package for variable selection for Bambi models. Kulprit is under active development so use it with care. If you find any bugs or have any feature requests, please open an issue.

Installation

Kulprit requires a working Python interpreter (3.10+). We recommend installing Python and key numerical libraries using the Anaconda Distribution, which has one-click installers available on all major platforms.

Assuming a standard Python environment is installed on your machine (including pip), Kulprit itself can be installed in one line using pip:

pip install kulprit

By default Kulprit performs a forward search, if you want to use Lasso (L1 search) you need to install scikit-learn package. You can install it using pip:

pip install kulprit[lasso]

Alternatively, if you want the bleeding edge version of the package you can install it from GitHub:

pip install git+https://github.com/bambinos/kulprit.git

Documentation

The Kulprit documentation can be found in the official docs. The examples provides a quick overview of variable selection and how this problem is tackled by Kulprit. A more detailed discussion of the theory, but also practical advice, we recommend you read the paper Advances in Projection Predictive Inference.

Contributions

Kulprit is a community project and welcomes contributions. Additional information can be found in the CONTRIBUTING.md page.

For a list of contributors see the GitHub contributor page

Citation

If you use Kulprit and want to cite it please use

@article{mclatchie2024, author = {Yann McLatchie and S{\"o}lvi R{\"o}gnvaldsson and Frank Weber and Aki Vehtari}, title = {{Advances in Projection Predictive Inference}}, volume = {40}, journal = {Statistical Science}, number = {1}, publisher = {Institute of Mathematical Statistics}, pages = {128 -- 147}, keywords = {Bayesian model selection, cross-validation, projection predictive inference}, year = {2025}, doi = {10.1214/24-STS949}, URL = {https://doi.org/10.1214/24-STS949} }

Donations

If you want to support Kulprit financially, you can make a donation to our sister project PyMC.

Code of Conduct

Kulprit wishes to maintain a positive community. Additional details can be found in the Code of Conduct

License

MIT License

Owner

  • Name: bambinos
  • Login: bambinos
  • Kind: organization

GitHub Events

Total
  • Create event: 19
  • Release event: 2
  • Issues event: 6
  • Watch event: 7
  • Delete event: 13
  • Issue comment event: 11
  • Push event: 73
  • Pull request event: 30
  • Fork event: 1
Last Year
  • Create event: 19
  • Release event: 2
  • Issues event: 6
  • Watch event: 7
  • Delete event: 13
  • Issue comment event: 11
  • Push event: 73
  • Pull request event: 30
  • Fork event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 15
  • Total pull requests: 74
  • Average time to close issues: 3 months
  • Average time to close pull requests: 8 days
  • Total issue authors: 3
  • Total pull request authors: 5
  • Average comments per issue: 0.13
  • Average comments per pull request: 0.62
  • Merged pull requests: 70
  • Bot issues: 0
  • Bot pull requests: 2
Past Year
  • Issues: 2
  • Pull requests: 23
  • Average time to close issues: N/A
  • Average time to close pull requests: 6 days
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.52
  • Merged pull requests: 21
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • aloctavodia (11)
  • yannmclatchie (3)
  • thedarredondo (1)
  • lucabol (1)
Pull Request Authors
  • aloctavodia (52)
  • yannmclatchie (21)
  • star1327p (4)
  • github-actions[bot] (2)
  • nsiccha (1)
Top Labels
Issue Labels
Pull Request Labels
enhancement (7) bug (3) documentation (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 337 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 5
  • Total maintainers: 3
pypi.org: kulprit

Kullback-Leibler projections for Bayesian model selection.

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 337 Last month
Rankings
Dependent packages count: 7.3%
Average: 37.9%
Dependent repos count: 68.4%
Maintainers (3)
aloctavodia tcapretto juanitorduz
Last synced: 6 months ago

Dependencies

pyproject.toml pypi
  • autoflake * develop
  • black * develop
  • flake8 * develop
  • flake8-bugbear * develop
  • flake8-builtins * develop
  • flake8-comprehensions * develop
  • flake8-debugger * develop
  • flake8-eradicate * develop
  • flake8-logging-format * develop
  • isort * develop
  • jupyter 1.0.0 develop
  • mkdocs-material * develop
  • mkdocstrings <0.19 develop
  • mknotebooks * develop
  • mypy * develop
  • pep8-naming * develop
  • pip ^22.0.3 develop
  • pre-commit * develop
  • pylint ^2.13.8 develop
  • pymdown-extensions * develop
  • pytest * develop
  • pytest-cov * develop
  • python-kacl * develop
  • pyupgrade * develop
  • tryceratops * develop
  • arviz >=0.11.2
  • bambi 0.9.0
  • numpy ^1.21.5
  • pandas ^1.3.5
  • pymc 4.0.0
  • python >=3.7.2, <3.10
  • scipy 1.7.3
  • torch ^1.11.0
.github/workflows/test.yml actions
  • ./.github/actions/python-poetry-env * composite
  • actions/checkout v2 composite
requirements-dev.txt pypi
  • black ==22.3.0 development
  • pre-commit >=2.19 development
  • pylint ==2.17.4 development
  • pytest >=4.4.0 development
  • pytest-cov >=2.6.1 development
requirements-docs.txt pypi
  • myst-nb *
  • pydata-sphinx-theme >=0.6.3
  • sphinx >=4
  • sphinx-copybutton *
.github/workflows/publish-to-test-pypi.yml actions
  • actions/checkout master composite
  • actions/setup-python v3 composite
  • pypa/gh-action-pypi-publish release/v1 composite