Metadata-Version: 2.1
Name: audmetric
Version: 1.1.3
Summary: Evaluate machine-learning models
Home-page: https://audeering.github.io/audmetric/
Author: Johannes Wagner, Hagen Wierstorf, Stephan Huber, Andreas Triantafyllopoulos, Uwe Reichel
Author-email: jwagner@audeering.com
License: MIT
Project-URL: Documentation, https://audeering.github.io/audmetric/
Keywords: mlops,machine learning
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Requires-Dist: audeer (>=1.1.0)
Requires-Dist: numpy

=========
audmetric
=========

|tests| |coverage| |docs| |python-versions| |license|

**audmetric** includes several equations
to estimate the performance of a machine learning prediction algorithm.

Some of the metrics are also available in sklearn_,
but we wanted to have a package
which depends only on numpy_.
For those metrics
we included tests that the results are identical to sklearn_.


.. _numpy: https://numpy.org/
.. _sklearn: https://scikit-learn.org/stable/


.. badges images and links:
.. |tests| image:: https://github.com/audeering/audmetric/workflows/Test/badge.svg
    :target: https://github.com/audeering/audmetric/actions?query=workflow%3ATest
    :alt: Test status
.. |coverage| image:: https://codecov.io/gh/audeering/audmetric/branch/master/graph/badge.svg?token=wOMLYzFnDO
    :target: https://codecov.io/gh/audeering/audmetric/
    :alt: code coverage
.. |docs| image:: https://img.shields.io/pypi/v/audmetric?label=docs
    :target: https://audeering.github.io/audmetric/
    :alt: audmetric's documentation
.. |license| image:: https://img.shields.io/badge/license-MIT-green.svg
    :target: https://github.com/audeering/audmetric/blob/master/LICENSE
    :alt: audmetric's MIT license
.. |python-versions| image:: https://img.shields.io/pypi/pyversions/audmetric.svg
    :target: https://pypi.org/project/audmetric/
    :alt: audmetric's supported Python versions

Changelog
=========

All notable changes to this project will be documented in this file.

The format is based on `Keep a Changelog`_,
and this project adheres to `Semantic Versioning`_.


Version 1.1.3 (2022/02/16)
--------------------------

* Added: reference for CCC formula
* Fixed: Support pandas series with datatype ``Int64``


Version 1.1.2 (2022/01/11)
--------------------------

* Fixed: typo in docstring of ``audmetric.mean_absolute_error()``


Version 1.1.1 (2022/01/03)
--------------------------

* Added: Python 3.9 support
* Removed: Python 3.6 support


Version 1.1.0 (2021/07/29)
--------------------------

* Added: ``audmetric.utils.infer_labels()``
* Added: ``audmetric.equal_error_rate()``
* Added: ``audmetric.detection_error_tradeoff()``


Version 1.0.1 (2021/06/10)
--------------------------

* Fixed: broken package due to missing ``__init_.py`` file


Version 1.0.0 (2021/06/09)
--------------------------

* Added: initial public release


.. _Keep a Changelog: https://keepachangelog.com/en/1.0.0/
.. _Semantic Versioning: https://semver.org/spec/v2.0.0.html


