{"id":14958402,"url":"https://github.com/robinthibaut/skbel","last_synced_at":"2025-10-05T18:40:41.071Z","repository":{"id":41385045,"uuid":"369214956","full_name":"robinthibaut/skbel","owner":"robinthibaut","description":"SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.","archived":false,"fork":false,"pushed_at":"2024-07-09T07:17:20.000Z","size":123906,"stargazers_count":24,"open_issues_count":0,"forks_count":4,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-12T23:02:12.448Z","etag":null,"topics":["bayesian-inference","gaussian-process","gaussian-process-regression","gaussian-processes","geology","groundwater","hydrogeology","machine-learning","multiple-output-regression","multivariate-regression","pfa","sklearn"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/robinthibaut.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":"CONTRIBUTING.md","funding":"FUNDING.yml","license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null},"funding":{"github":["robinthibaut"]}},"created_at":"2021-05-20T13:19:16.000Z","updated_at":"2024-12-03T14:57:01.000Z","dependencies_parsed_at":"2023-01-30T08:30:48.659Z","dependency_job_id":"dd377a34-e0ba-41ce-815d-77ec72fd037c","html_url":"https://github.com/robinthibaut/skbel","commit_stats":{"total_commits":579,"total_committers":3,"mean_commits":193.0,"dds":"0.010362694300518172","last_synced_commit":"893579332c15abf632920071d90b95e7b938f015"},"previous_names":[],"tags_count":7,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/robinthibaut%2Fskbel","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/robinthibaut%2Fskbel/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/robinthibaut%2Fskbel/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/robinthibaut%2Fskbel/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/robinthibaut","download_url":"https://codeload.github.com/robinthibaut/skbel/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248643011,"owners_count":21138354,"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","gaussian-process","gaussian-process-regression","gaussian-processes","geology","groundwater","hydrogeology","machine-learning","multiple-output-regression","multivariate-regression","pfa","sklearn"],"created_at":"2024-09-24T13:16:58.198Z","updated_at":"2025-10-05T18:40:40.972Z","avatar_url":"https://github.com/robinthibaut.png","language":"Python","funding_links":["https://github.com/sponsors/robinthibaut"],"categories":["Python"],"sub_categories":["General-Purpose Machine Learning"],"readme":".. -*- mode: rst -*-\n\n|Travis|_  |Doc|_ |Black|_ |PythonVersion|_ |PyPi|_ |DOI|_ |Downloads|_\n\n.. |Travis| image:: https://travis-ci.com/robinthibaut/skbel.svg?branch=master\n.. _Travis: https://travis-ci.com/robinthibaut/skbel\n\n.. |Doc| image:: https://readthedocs.org/projects/skbel/badge/?version=latest\n.. _Doc: https://skbel.readthedocs.io/en/latest/?badge=latest\n\n.. |CodeCov| image:: https://codecov.io/gh/robinthibaut/skbel/branch/main/graph/badge.svg?token=S0T9NW3VK6\n.. _CodeCov: https://codecov.io/gh/robinthibaut/skbel\n\n.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/skbel\n.. _PythonVersion: https://img.shields.io/pypi/pyversions/skbel\n\n.. |PyPi| image:: https://badge.fury.io/py/skbel.svg\n.. _PyPi: https://badge.fury.io/py/skbel\n\n.. |Black| image:: https://img.shields.io/badge/code%20style-black-000000.svg\n.. _Black: https://github.com/psf/black\n\n.. |DOI| image:: https://zenodo.org/badge/369214956.svg\n.. _DOI: https://zenodo.org/badge/latestdoi/369214956\n\n.. |Downloads| image:: https://pepy.tech/badge/skbel\n.. _Downloads: https://pepy.tech/project/skbel\n\n.. |PythonMinVersion| replace:: 3.7\n.. |NumPyMinVersion| replace:: 1.14.6\n.. |SciPyMinVersion| replace:: 1.1.0\n.. |JoblibMinVersion| replace:: 0.11\n.. |MatplotlibMinVersion| replace:: 2.2.2\n.. |Scikit-ImageMinVersion| replace:: 0.24.1\n.. |PandasMinVersion| replace:: 0.25.0\n.. |SeabornMinVersion| replace:: 0.9.0\n.. |PytestMinVersion| replace:: 5.0.1\n\n.. image:: https://raw.githubusercontent.com/robinthibaut/skbel/master/docs/img/illu-01.png\n\n**skbel** is a Python module for implementing the Bayesian Evidential Learning framework built on top of\nscikit-learn and is distributed under the 3-Clause BSD license.\n\nFor more information, read the `documentation \u003chttps://skbel.readthedocs.io/en/latest/\u003e`_ and run the example `notebook \u003chttps://www.kaggle.com/dsv/2648718\u003e`_.\n\nInstallation\n------------\n\nDependencies\n~~~~~~~~~~~~\n\nskbel requires:\n\n- Python (\u003e= |PythonMinVersion|)\n- Scikit-Learn (\u003e= |Scikit-ImageMinVersion|)\n- NumPy (\u003e= |NumPyMinVersion|)\n- SciPy (\u003e= |SciPyMinVersion|)\n- joblib (\u003e= |JoblibMinVersion|)\n\n=======\n\nSkbel plotting capabilities require Matplotlib (\u003e= |MatplotlibMinVersion|).\n\nUser installation\n~~~~~~~~~~~~~~~~~\n\nThe easiest way to install skbel is using ``pip``   ::\n\n    pip install skbel\n\n\nDevelopment\n-----------\n\nWe welcome new contributors of all experience levels.\n\nImportant links\n~~~~~~~~~~~~~~~\n\n- Official source code repo: https://github.com/robinthibaut/skbel/\n- Download releases: https://pypi.org/project/skbel/\n- Issue tracker: https://github.com/robinthibaut/skbel/issues\n\nSource code\n~~~~~~~~~~~\n\nYou can check the latest sources with the command::\n\n    git clone https://github.com/robinthibaut/skbel.git\n\nContributing\n~~~~~~~~~~~~\n\nContributors and feedback from users are welcome. Don't hesitate to submit an issue or a PR, or request a new feature.\n\n\nTesting\n~~~~~~~\n\nAfter installation, you can launch the test suite from outside the source\ndirectory (you will need to have ``pytest`` \u003e= |PyTestMinVersion| installed)::\n\n    pytest skbel\n\n\nHelp and Support\n----------------\n\nDocumentation\n~~~~~~~~~~~~~\n\n- HTML documentation (latest release): https://skbel.readthedocs.io/en/latest/\n\nCommunication\n~~~~~~~~~~~~~\n\n- Github Discussions: https://github.com/robinthibaut/skbel/discussions\n\nHow to cite\n----------------\n\nThibaut, Robin, \u0026 Maximilian Ramgraber. (2021). SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn (v2.0.0). Zenodo. https://doi.org/10.5281/zenodo.6205242\n\nBibTeX::\n\n    @software{thibaut_skbel_2021,\n    author       = {Thibaut, Robin and Maximilian Ramgraber},\n    title        = {{SKBEL} - Bayesian Evidential Learning framework built on top of scikit-learn},\n    month        = {9},\n    year         = 2021,\n    publisher    = {Zenodo},\n    version      = {v2.0.0},\n    doi          = {10.5281/zenodo.6205242},\n    url          = {https://doi.org/10.5281/zenodo.6205242},\n    }\n\nNotebooks and tutorials\n------------------------\n\nNolwenn Lesparre, Nicolas Compaire, Thomas Hermans and Robin Thibaut. (2022). 4D Temperature Monitoring with BEL. [Dataset]. Kaggle. doi: 10.34740/kaggle/ds/2275519. url: https://doi.org/10.34740/kaggle/ds/2275519\n\nThibaut, Robin (2021). WHPA Prediction. [Dataset]. Kaggle. doi:10.34740/kaggle/dsv/2648718. url: https://www.kaggle.com/dsv/2648718\n\nPeer-reviewed publications using SKBEL\n--------------------------------------\n\nThibaut, Robin, Nicolas Compaire, Nolwenn Lesparre, Maximilian Ramgraber, Eric Laloy, and Thomas Hermans (Nov. 2022). “Comparing Well and Geophysical Data for Temperature Monitoring Within a Bayesian Experimental Design Framework”. In: Water Resources Research 58 (11). issn: 0043-1397. doi: 10.1029/2022WR033045. url: https://onlinelibrary.wiley.com/doi/10.1029/2022WR033045.\n\nThibaut, Robin, Eric Laloy, and Thomas Hermans (Dec. 2021). “A new framework for experimental design using Bayesian Evidential Learning: The case of wellhead protection area”. In: Journal of Hydrology 603, p. 126903. issn: 00221694. doi: 10.1016/j.jhydrol.2021.126903. url: https://linkinghub.elsevier.com/retrieve/pii/S0022169421009537.\n\nResearch project\n----------------\n\nLogs and results of the research project are available on the `project page \u003chttps://www.researchgate.net/project/A-new-framework-for-Experimental-Design-in-Earth-Sciences-using-Bayesian-Evidential-Learning-BEL4ED\u003e`_.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frobinthibaut%2Fskbel","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frobinthibaut%2Fskbel","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frobinthibaut%2Fskbel/lists"}