def classify (data, features = nil)
      raise "Untrained model" unless (@fv_test)
  
      data_point = Eluka::DataPoint.new(data, @analyzer)
      @fv_test.add(data_point.vector)
  
      File.open(@directory + "/classify", "w") do |f| f.puts @fv_test.to_libSVM(features) end
      output = `#{@svm_predict_path} #{@directory}/classify #{@directory}/model #{@directory}/result`
      
      puts output if (@verbose)
  
      return @labels.lookup( File.open( @directory + "/result", "r" ).read.to_i )
    end
def classify (data, features = nil)
      raise "Untrained model" unless (@fv_test)
  
      data_point = Eluka::DataPoint.new(data, @analyzer)
      @fv_test.add(data_point.vector)
  
      File.open(@directory + "/classify", "w") do |f| f.puts @fv_test.to_libSVM(features) end
      output = `#{@svm_predict_path} #{@directory}/classify #{@directory}/model #{@directory}/result`
      
      puts output if (@verbose)
  
      return @labels.lookup( File.open( @directory + "/result", "r" ).read.to_i )
    end
Classify a data point