class Newral::Networks::BackpropagationNetwork

Public Class Methods

new( number_of_inputs:2, number_of_hidden:2, number_of_outputs:2 ) click to toggle source
Calls superclass method
# File lib/newral/networks/backpropagation_network.rb, line 8
def initialize( number_of_inputs:2, number_of_hidden:2, number_of_outputs:2 )
  super()
  add_layer "hidden" do 
    number_of_hidden.times do |idx|
      add_neuron "hidden_#{idx}", weight_length:number_of_inputs
    end 
  end

  
  add_layer "output" do 
    number_of_outputs.times do |idx|
      add_neuron "output_#{idx}", weight_length:number_of_hidden
    end 
  end
  
  # in this network all hidden neurons link to all output neurons
  @layers["hidden"].neurons.each do |hidden_neuron|
    @layers["output"].neurons.each  do |output_neuron|
      output_neuron.add_input hidden_neuron
    end 
  end
end

Public Instance Methods

output_weights( neuron ) click to toggle source

gets the weights of the output neurons this input feeds to this of course can be done much simpler (as its always the nth weight of the output neuron) however we want to stay explicit

# File lib/newral/networks/backpropagation_network.rb, line 54
def output_weights( neuron )
  raise Errors::OnlyPossibleForHidden unless @layers["hidden"].neurons.member?( neuron )
  weights = []
  @layers["output"].neurons.each do |output_neuron|
    output_neuron.inputs.each_with_index do |input,idx| 
      weights << output_neuron.weights[ idx ] if input == neuron
    end 
  end 
 weights 
end
train( input: [], output: [] ) click to toggle source

gets an array of inputs and the corresponding expected outputs first we update our output layer then our hidden layer

# File lib/newral/networks/backpropagation_network.rb, line 35
def train( input: [], output: [] )
  before_error =  calculate_error( input: input,output: output )
  input.each_with_index do |input,idx| 
    calculated_output = update_with_vector( input )
    @layers["output"].neurons.each_with_index do |neuron,neuron_idx|
      neuron.adjust_weights( expected: output[ idx ][ neuron_idx ])
    end 

    @layers["hidden"].neurons.each do |neuron|
      neuron.adjust_weights( expected: output[ idx ], layer: :hidden, output: calculated_output, weights_at_output_nodes: output_weights( neuron ))
    end 
  end
  new_error =  calculate_error( input: input,output: output )
  before_error-new_error
end