Rumale::SVM

Rumale::SVM provides support vector machine algorithms using LIBSVM and LIBLINEAR with Rumale interface.

Add this line to your application's Gemfile:

gem 'rumale-svm'

And then execute:

$ bundle

Or install it yourself as:

$ gem install rumale-svm

• Rumale::SVM API Documentation

Download pendigits dataset from LIBSVM DATA web page.

$ wget https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass/pendigits
$ wget https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass/pendigits.t

Training linear support vector classifier.

require 'rumale/svm'
require 'rumale/dataset'

samples, labels = Rumale::Dataset.load_libsvm_file('pendigits')
svc = Rumale::SVM::LinearSVC.new(random_seed: 1)
svc.fit(samples, labels)

File.open('svc.dat', 'wb') { |f| f.write(Marshal.dump(svc)) }

Evaluate classifiction accuracy on testing datase.

require 'rumale/svm'
require 'rumale/dataset'

samples, labels = Rumale::Dataset.load_libsvm_file('pendigits.t')
svc = Marshal.load(File.binread('svc.dat'))

puts "Accuracy: #{svc.score(samples, labels).round(3)}"

Execution result.

$ ruby rumale_svm_train.rb
$ ls svc.dat
svc.dat
$ ruby rumale_svm_test.rb
Accuracy: 0.835

Bug reports and pull requests are welcome on GitHub at https://github.com/yoshoku/rumale-svm. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.

The gem is available as open source under the terms of the BSD-3-Clause License.