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Naive SVM library in Python

Project Description

=======
SVMPy
=======

By Andrew Tulloch (http://tullo.ch)

--------------
Introduction
--------------

This is a basic implementation of a soft-margin kernel SVM solver in
Python using `numpy` and `cvxopt`.

See http://tullo.ch/articles/svm-py/ for a description of the
algorithm used and the general theory behind SVMs.

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Demonstration
--------------

Run `bin/svm-py-demo --help`.

::

∴ bin/svm-py-demo --help
usage: svm-py-demo [-h] [--num-samples NUM_SAMPLES]
[--num-features NUM_FEATURES] [-g GRID_SIZE] [-f
FILENAME]

optional arguments:
-h, --help show this help message and exit
--num-samples NUM_SAMPLES
--num-features NUM_FEATURES
-g GRID_SIZE, --grid-size GRID_SIZE
-f FILENAME, --filename FILENAME


For example,

::

bin/svm-py-demo --num-samples=100 --num-features=2 --grid-size=500 --filename=svm500.pdf

yields the image

.. image:: http://i.imgur.com/yy0oUVk.png

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