module TLearn

Constants

VERSION

Public Class Methods

add_noise_data(data,noise_rate) click to toggle source

add noise to sample datas¶ ↑

@param data Array data which we want to add noise @param noise_rate float rate of noise

# File lib/t_learn/hop_field_net.rb, line 103
def TLearn.add_noise_data(data,noise_rate)
  data_with_noise = Marshal.load(Marshal.dump(data))
  data.size.times do |n|
    if rand <= noise_rate
      if data_with_noise[n] == -1.0
        data_with_noise[n] = 1.0
      else
        data_with_noise[n] = -1.0
      end
    end
  end

  return data_with_noise
end

evaluate(teacher_data,data) click to toggle source

evaluate predict data with teatcher data¶ ↑

# File lib/t_learn/hop_field_net.rb, line 121
def TLearn.evaluate(teacher_data,data)
  dominator = 0.0
  molecule = 0.0 
  teacher_data.zip(data).each do |td,d|
    dominator += 1 
    molecule += 1 if td == d
  end

  return (molecule/dominator)*100
end