Machine Learning example using libsvm

machine_learning.rb

#gem install rb-libsvm

require 'libsvm'

class Predictor

   def initialize

		parameter = Libsvm::SvmParameter.new
		parameter.cache_size = 3 # in megabytes
		parameter.eps = 0.001
		parameter.c = 10

		examples = [ [1,0,1], [-1,0,-1] ].map {|ary| Libsvm::Node.features(ary) }
		labels = [ 3 , 7 ]

		problem = Libsvm::Problem.new
		problem.set_examples(labels, examples)

		@model = Libsvm::Model.train(problem, parameter)

   end
   def sayHi
      
	  pred = @model.predict(Libsvm::Node.features(1, 0, 1))
	  puts "Example [1, 1, 1] - Predicted #{pred}"
	  
	  pred = @model.predict(Libsvm::Node.features(-1, 0, -1))
	  puts "Example [-1, 0, -1] - Predicted #{pred}"
	  
	  pred = @model.predict(Libsvm::Node.features(-10, 0, 25))
	  puts "Example [-10, 0, 25] - Predicted #{pred}"
	  
	  pred = @model.predict(Libsvm::Node.features(12, 0, 30))
	  puts "Example [12, 0, 30] - Predicted #{pred}"
	  
	  pred = @model.predict(Libsvm::Node.features(65, 0, -54))
	  puts "Example [65, 0, -54] - Predicted #{pred}"
	  
   end
end

hello = Predictor.new()
hello.sayHi