libsvm-ruby-swig¶ ↑
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Ruby interface to LIBSVM (using SWIG)
DESCRIPTION:¶ ↑
This is the Ruby port of the LIBSVM Python SWIG (Simplified Wrapper and Interface Generator) interface.
A slightly modified version of LIBSVM 2.9 is included, it allows turrning on/off the debug log. You don’t need your own copy of SWIG to use this library - all needed files are generated using SWIG already.
Look for the README file in the ruby subdirectory for instructions. The binaries included were built under Ubuntu Linux 2.6.28-18-generic x86_64, you should run make under the libsvm-2.9 and libsvm-2.9/ruby directories to regenerate the executables for your environment.
LIBSVM is in use at tweetsentiments.com - A Twitter / Tweet sentiment analysis application
INSTALL:¶ ↑
Currently the gem is available on linux only(tested on Ubuntu 8-9 and Fedora 9-12, and on OS X by danielsdeleo), and you will need g++ installed to compile the native code.
sudo gem sources -a http://gems.github.com (you only have to do this once) sudo gem install tomz-libsvm-ruby-swig
SYNOPSIS:¶ ↑
Quick Interactive Tutorial using irb (adopted from the python code from Toby Segaran’s “Programming Collective Intelligence” book):
irb(main):001:0> require 'svm'
=> true
irb(main):002:0> prob = Problem.new([1,-1],[[1,0,1],[-1,0,-1]])
irb(main):003:0> param = Parameter.new(:kernel_type => LINEAR, :C => 10)
irb(main):004:0> m = Model.new(prob,param)
irb(main):005:0> m.predict([1,1,1])
=> 1.0
irb(main):006:0> m.predict([0,0,1])
=> 1.0
irb(main):007:0> m.predict([0,0,-1])
=> -1.0
irb(main):008:0> m.save("test.model")
irb(main):009:0> m2 = Model.new("test.model")
irb(main):010:0> m2.predict([0,0,-1])
=> -1.0
AUTHOR:¶ ↑
Tom Zeng
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tom.z.zeng at gmail dot com