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Naive SVM library in Python

Project description

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

Project details


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Filename, size & hash SHA256 hash help File type Python version Upload date
svmpy-0.3.macosx-10.8-x86_64.exe (66.9 kB) Copy SHA256 hash SHA256 Windows Installer any Nov 26, 2013
svmpy-0.3.tar.gz (3.9 kB) Copy SHA256 hash SHA256 Source None Nov 26, 2013

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