Metadata-Version: 1.0
Name: featureforge
Version: 0.1
Summary: A library to build and test machine learning features
Home-page: https://github.com/machinalis/featureforge
Author: Rafael Carrascosa, Daniel Moisset, Javier Mansilla
Author-email: rcarrascosa@machinalis.com
License: UNKNOWN
Description: Feature Forge
        =============
        
        This library provides a set of tools that can be useful in many machine
        learning applications (classification, clustering, regression, etc.), and
        particularly helpful if you use scikit-learn (although this can work if
        you have a different algorithm).
        
        Most machine learning problems involve an step of feature definition and
        preprocessing. Feature Forge helps you with:
        
         * Defining and documenting features
         * Testing your features against specified cases and against randomly generated
           cases (stress-testing). This helps you making your application more robust
           against invalid/misformatted input data. This also helps you checking that
           low-relevance results when doing feature analysis is actually because the
           feature is bad, and not because there's a slight bug in your feature code.
         * Evaluating your features on a data set, producing a feature evaluation
           matrix. The evaluator has a robust mode that allows you some tolerance both
           for invalid data and buggy features.
        
        Documentation
        -------------
        
        Documentation is available at http://feature-forge.readthedocs.org/en/latest/
        
        Contact information
        -------------------
        
        Feature Forge is © 2014 Machinalis (http://www.machinalis.com/). Its primary
        authors are:
        
         * Javier Mansilla <jmansilla@machinalis.com> (jmansilla at github)
         * Daniel Moisset <dmoisset@machinalis.com> (dmoisset at github)
         * Rafael Carrascosa <rcarrascosa@machinalis.com> (rafacarrascosa at github)
        
        Any contributions or suggestions are welcome, the official channel for this is
        submitting github pull requests or issues.
        
        Changelog
        ---------
        
        0.1: Initial release
        
Platform: UNKNOWN
