svm

svmpy

Basic soft-margin kernel SVM implementation in Python

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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.


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

.. image:: https://d2weczhvl823v0.cloudfront.net/ajtulloch/svmpy/trend.png :alt: Bitdeli badge :target: https://bitdeli.com/free

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