Metadata-Version: 2.1
Name: calfcv
Version: 0.0.3
Summary: Coarse approximation linear function with cross validation
Home-page: 
Download-URL: https://github.com/scikit-learn-contrib/project-template
Maintainer: Carlson Research, LLC
Maintainer-email: hrolfrc@gmail.com
License: new BSD
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: License :: OSI Approved
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
License-File: LICENSE

.. -*- mode: rst -*-

|Travis|_ |AppVeyor|_ |Codecov|_ |CircleCI|_ |ReadTheDocs|_

.. |Travis| image:: https://travis-ci.org/scikit-learn-contrib/project-template.svg?branch=master
.. _Travis: https://travis-ci.org/scikit-learn-contrib/project-template

.. |AppVeyor| image:: https://ci.appveyor.com/api/projects/status/coy2qqaqr1rnnt5y/branch/master?svg=true
.. _AppVeyor: https://ci.appveyor.com/project/glemaitre/project-template

.. |Codecov| image:: https://codecov.io/gh/scikit-learn-contrib/project-template/branch/master/graph/badge.svg
.. _Codecov: https://codecov.io/gh/scikit-learn-contrib/project-template

.. |CircleCI| image:: https://circleci.com/gh/scikit-learn-contrib/project-template.svg?style=shield&circle-token=:circle-token
.. _CircleCI: https://circleci.com/gh/scikit-learn-contrib/project-template/tree/master

.. |ReadTheDocs| image:: https://readthedocs.org/projects/sklearn-template/badge/?version=latest
.. _ReadTheDocs: https://sklearn-template.readthedocs.io/en/latest/?badge=latest

CalfCV
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.. _scikit-learn: https://scikit-learn.org

This is a Python implementation of the Coarse Approximation Linear Function (CALF) used in the R package, calf_. The calfcv package follows the conventions of Scikit-Learn and is compatible with that ecosystem.

.. _calf: https://cran.r-project.org/web/packages/CALF/index.html

Jeffries, C.D., Ford, J.R., Tilson, J.L. et al. A greedy regression algorithm with coarse weights offers novel advantages. Sci Rep 12, 5440 (2022). https://doi.org/10.1038/s41598-022-09415-2



