{"id":20405501,"url":"https://github.com/bambinos/kulprit","last_synced_at":"2025-05-07T19:09:39.534Z","repository":{"id":37014267,"uuid":"460460176","full_name":"bambinos/kulprit","owner":"bambinos","description":"Kullback-Leibler projections for Bayesian model selection in Python","archived":false,"fork":false,"pushed_at":"2025-04-14T11:14:27.000Z","size":5084,"stargazers_count":34,"open_issues_count":5,"forks_count":5,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-05-07T19:06:51.039Z","etag":null,"topics":["bayesian-inference","kullback-leibler-divergence","model-selection"],"latest_commit_sha":null,"homepage":"https://kulprit.readthedocs.io","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bambinos.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":null,"code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2022-02-17T14:03:16.000Z","updated_at":"2025-05-05T22:11:55.000Z","dependencies_parsed_at":"2024-03-20T21:43:47.467Z","dependency_job_id":"16b64cfb-abb5-4b37-8fb1-b04e31bffda2","html_url":"https://github.com/bambinos/kulprit","commit_stats":null,"previous_names":["yannmclatchie/kulprit"],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bambinos%2Fkulprit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bambinos%2Fkulprit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bambinos%2Fkulprit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bambinos%2Fkulprit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bambinos","download_url":"https://codeload.github.com/bambinos/kulprit/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252940935,"owners_count":21828769,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bayesian-inference","kullback-leibler-divergence","model-selection"],"created_at":"2024-11-15T05:11:36.020Z","updated_at":"2025-05-07T19:09:39.458Z","avatar_url":"https://github.com/bambinos.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cimg src=\"https://raw.githubusercontent.com/bambinos/kulprit/main/docs/logos/kulprit_flat.png\" width=200\u003e\u003c/img\u003e\n\nKullback-Leibler projections for Bayesian model selection in Python.\n\n[![PyPi version](https://badge.fury.io/py/kulprit.svg)](https://badge.fury.io/py/kulprit)\n[![Build Status](https://github.com/bambinos/kulprit/actions/workflows/test.yml/badge.svg)](https://github.com/bambinos/kulprit/actions/workflows/test.yml)\n[![codecov](https://codecov.io/gh/bambinos/kulprit/branch/main/graph/badge.svg?token=SLJIK2O4C5)](https://codecov.io/gh/bambinos/kulprit)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)\n\n\n## Overview\n\nKulprit _(Pronounced: kuːl.prɪt)_ is a package for variable selection for [Bambi](https://github.com/bambinos/bambi) models.\nKulprit is under active development so use it with care. If you find any bugs or have any feature requests, please open an [issue](https://github.com/bambinos/kulprit/issues).\n\n\n## Installation\n\nKulprit requires a working Python interpreter (3.10+). We recommend installing Python and key numerical libraries using the [Anaconda Distribution](https://www.anaconda.com/products/individual#Downloads), which has one-click installers available on all major platforms.\n\nAssuming a standard Python environment is installed on your machine (including pip), Kulprit itself can be installed in one line using pip:\n\n    pip install kulprit\n\nBy 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:\n\n    pip install kulprit[lasso]\n\nAlternatively, if you want the bleeding edge version of the package you can install it from GitHub:\n\n    pip install git+https://github.com/bambinos/kulprit.git\n\n## Documentation\n\nThe Kulprit documentation can be found in the [official docs](https://kulprit.readthedocs.io/en/latest/). 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](https://doi.org/10.1214/24-STS949).\n\n\n## Contributions\n\nKulprit is a community project and welcomes contributions. Additional information can be found in the [CONTRIBUTING.md](https://github.com/bambinos/kulprit/blob/main/CONTRIBUTING.md) page.\n\nFor a list of contributors see the [GitHub contributor](https://github.com/bambinos/kulprit/graphs/contributors) page\n\n## Citation\n\nIf you use Kulprit and want to cite it please use\n\n```\n@article{mclatchie2024,\n    author = {Yann McLatchie and S{\\\"o}lvi R{\\\"o}gnvaldsson and Frank Weber and Aki Vehtari},\n    title = {{Advances in Projection Predictive Inference}},\n    volume = {40},\n    journal = {Statistical Science},\n    number = {1},\n    publisher = {Institute of Mathematical Statistics},\n    pages = {128 -- 147},\n    keywords = {Bayesian model selection, cross-validation, projection predictive inference},\n    year = {2025},\n    doi = {10.1214/24-STS949},\n    URL = {https://doi.org/10.1214/24-STS949}\n}\n```\n\n\n## Donations\n\nIf you want to support Kulprit financially, you can [make a donation](https://numfocus.org/donate-to-pymc) to our sister project PyMC.\n\n## Code of Conduct\n\nKulprit wishes to maintain a positive community. Additional details can be found in the [Code of Conduct](https://github.com/bambinos/kulprit/blob/main/docs/CODE_OF_CONDUCT.md)\n\n## License\n\n[MIT License](https://github.com/bambinos/kulprit/blob/main/LICENSE)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbambinos%2Fkulprit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbambinos%2Fkulprit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbambinos%2Fkulprit/lists"}