Metadata-Version: 2.1
Name: gmd
Version: 0.0.1
Summary: A scikit-learn compatible python/cython implementation of the GMD algorithm.
Home-page: https://github.com/FlopsKa/gmd
Maintainer: Florian Kalinke
Maintainer-email: flops.ka@gmail.com
License: MIT
Download-URL: https://github.com/FlopsKa/gmd
Description: .. -*- mode: rst -*-
        
        |Travis|_ |AppVeyor|_ |Codecov|_ |CircleCI|_ |ReadTheDocs|_
        
        .. |Travis| image:: https://travis-ci.com/FlopsKa/gmd.svg?branch=master
        .. _Travis: https://travis-ci.com/FlopsKa/gmd
        
        .. |AppVeyor| image:: https://ci.appveyor.com/api/projects/status/84j8gekk5ob3i28d/branch/master?svg=true
        .. _AppVeyor: https://ci.appveyor.com/project/FlopsKa/gmd/
        
        .. |Codecov| image:: https://codecov.io/gh/FlopsKa/gmd/branch/master/graph/badge.svg
        .. _Codecov: https://codecov.io/gh/FlopsKa/gmd
        
        .. |CircleCI| image:: https://circleci.com/gh/FlopsKa/gmd.svg?style=shield&circle-token=:circle-token
        .. _CircleCI: https://circleci.com/gh/FlopsKa/gmd/tree/master
        
        .. |ReadTheDocs| image:: https://readthedocs.org/projects/gmd/badge/?version=latest
        .. _ReadTheDocs: https://gmd.readthedocs.io/en/latest/?badge=latest
        
        Scikit-learn Greedy Maximum Deviation (GMD) Algorithm
        =====================================================
        
        .. _scikit-learn: https://scikit-learn.org
        
        This project provides a `scikit-learn`_ compatible python implementation of the
        algorithm presented in [`Trittenbach2018`_] together with some usage examples
        and a reproduction of the results from the paper.
        
        Recent approaches in outlier detection seperate the subspace search from the
        actual outlier detection and run the outlier detection algorithm on a
        projection of the original feature space. See [`Keller2012`_]. As a result the
        detection algorithm (Local Outlier Factor is used in the paper) does not suffer
        from the curse of dimensionality.
        
        
        .. _Trittenbach2018: https://link.springer.com/article/10.1007/s41060-018-0137-7
        .. _Keller2012: https://ieeexplore.ieee.org/document/6228154
        
        .. _documentation: https://gmd.readthedocs.io/en/latest/
        
        Refer to the documentation_ to see usage examples.
        
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python :: 3.7
Provides-Extra: docs
Provides-Extra: tests
