Metadata-Version: 1.1
Name: brew
Version: 0.1.1
Summary: BREW: Python Multiple Classifier System API
Home-page: https://github.com/viisar/brew
Author: Dayvid Victor <victor.dvro@gmail.com>, Thyago Porpino <thyago.porpino@gmail.com>
Author-email: brew-python-devs@googlegroups.com
License: MIT
Description: =============================
        brew
        =============================
        
        .. image:: https://badge.fury.io/py/brew.png
            :target: http://badge.fury.io/py/brew
        
        .. image:: https://travis-ci.org/viisar/brew.png?branch=master
            :target: https://travis-ci.org/viisar/brew
        
        .. image:: https://pypip.in/d/brew/badge.png
            :target: https://pypi.python.org/pypi/brew
        
        .. image:: https://pypip.in/d/brew/badge.png
            :target: https://testpypi.python.org/pypi/brew
        
        
        BREW: A Multiple Classifier Systems API
        
        This project was started in 2014 by Dayvid Victor and Thyago Porpino for the project of the Multiple Classifier Systems class at Federal University of Pernambuco.
        
        The aim of this project is to provide a structure for Ensemble Generation, Ensemble Pruning, and Static and Dynamic selection of classifiers.
        
        
        Dependencies
        ============
        - Python 2.6+
        - scikit-learn >= 0.14.1
        - Numpy >= 1.3
        - SciPy >= 0.7
        - Matplotlib >= 0.99.1 (for examples, only)
        
        Features
        --------
        * Dynamic Classifier Selection: OLA, LCA, A Priori, A Posteriori.
        * Dynamic Ensemble Selection: KNORA E and KNORA U.
        * Oversampling: SMOTE.
        * Ensemble Combination Rules: majority vote, min, max, mean and median.
        * Ensemble Diversity Metrics: Entropy Measure E, Kohavi Wolpert Variance, Q Statistics, Correlation Coefficient p, Disagreement Measure, Agreement Measure, Double Fault Measure.
        * Ensemble Classifier Generators: Bagging (sklearn wrapper), Random Subspace (sklearn wrapper), SMOTE Bagging.
        
        
        Important References
        ====================
        
        - Kuncheva, Ludmila I. Combining pattern classifiers: methods and algorithms. John Wiley & Sons, 2014.
        
        - Zhou, Zhi-Hua. Ensemble methods: foundations and algorithms. CRC Press, 2012.
        
        
        
        
        Documentation
        -------------
        
        The full documentation is at http://brew.rtfd.org.
        
        
        
        History
        -------
        
        0.1.0 (2014-11-12)
        ++++++++++++++++++
        
        * First release on PyPI.
        
Keywords: brew
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering
