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Naive SVM library in Python

Project Description

By Andrew Tulloch (


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

See for a description of the algorithm used and the general theory behind SVMs.


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

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

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
svmpy-0.3.macosx-10.8-x86_64.exe (66.9 kB) Copy SHA256 Checksum SHA256 any Windows Installer Nov 26, 2013
svmpy-0.3.tar.gz (3.9 kB) Copy SHA256 Checksum SHA256 Source Nov 26, 2013

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