Basic soft-margin kernel SVM implementation in Python
Python
Latest commit ff7b138 Mar 30, 2016 @ajtulloch Merge pull request #3 from addvaluejack/master
Add radial basis function kernel
Permalink
Failed to load latest commit information.
bin Added demonstration to VC Nov 26, 2013
svmpy Add radial basis function kernel Mar 30, 2016
MANIFEST.in Updated MANIFEST Nov 26, 2013
README.rst Add a Bitdeli badge to README Dec 17, 2013
setup.py Update README Nov 26, 2013

README.rst

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

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

Bitdeli badge