Metadata-Version: 1.0
Name: milk
Version: 0.2
Summary: Machine Learning Toolkit
Home-page: http://luispedro.org/software/milk
Author: Luis Pedro Coelho
Author-email: lpc@cmu.edu
License: MIT
Description: Milk is a machine learning toolkit in Python. Its focus is on supervised classification.
        
        milk wraps libsvm in a Pythonic way (the models learned have weight arrays that
        are accessible from Python directly, the models are pickle()able, you can pass
        any Python function as a kernel,....)
        
        It also supports k-means clustering with an implementation that is careful not
        to use too much memory (if your dataset fits into memory, milk can cluster it).
        
        It does not have its own file format or in-memory format, which I consider a
        feature as it works on numpy arrays directly (or anything that is convertible to
        a numpy-array) without forcing you to copy memory around. For SVMs, you can even
        just use any datatype if you have your own kernel function.
        
        Features
        --------
        - SVMs. Using the libsvm solver with a pythonesque wrapper around it.
        - Stepwise Discriminant Analysis for feature selection.
        - K-means using as little memory as possible.
        
        License: MIT
        Author: Luis Pedro Coelho (with code from LibSVM)
        Website: `http://luispedro.org/software/milk <http://luispedro.org/software/milk>`_
        
Platform: UNKNOWN
