Class: Newral::Networks::Sigmoid

Inherits:
Perceptron show all
Defined in:
lib/newral/networks/sigmoid.rb

Instance Attribute Summary

Attributes inherited from Perceptron

#bias, #inputs, #last_output, #weights

Instance Method Summary collapse

Methods inherited from Perceptron

#add_input, #calculate_input, #calculate_value, #initialize, #move, #number_of_directions, #set_weights_and_bias, #update_with_vector

Constructor Details

This class inherits a constructor from Newral::Networks::Perceptron

Instance Method Details

#adjust_weights(expected: nil, learning_rate: 0.5, layer: :output, weights_at_output_nodes: nil, output: nil) ⇒ Object

depending on where the neuron is placed we need other infos to adjust the weights on output we just need the expected results for hidden neurons we also need to know the weights at the output nodes and the actual output of the network



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# File 'lib/newral/networks/sigmoid.rb', line 45

def adjust_weights( expected: nil, learning_rate:0.5, layer: :output, weights_at_output_nodes: nil, output: nil )
  error_delta = layer.to_sym == :output ?  delta_rule( expected: expected ) : delta_rule_hidden( output: output, expected: expected, weights_at_output_nodes: weights_at_output_nodes )
  @weights.each_with_index do |weight,idx|
    @weights[idx] = @weights[idx]-error_delta[ idx ]*learning_rate
  end 
end

#delta_rule(expected: nil) ⇒ Object

if you want to know how this works visit mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/



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# File 'lib/newral/networks/sigmoid.rb', line 12

def delta_rule( expected: nil )
  error_delta = []
  @weights.each_with_index do |weight,idx|
    input = calculate_input(  @inputs[ idx ] )
    error_delta << -(expected-output)*(output)*(1-output )*input
  end
  error_delta
end

#delta_rule_hidden(output: nil, expected: nil, weights_at_output_nodes: nil) ⇒ Object

this just works for 1 hidden layer stats.stackexchange.com/questions/70168/back-propagation-in-neural-nets-with-2-hidden-layers bias also not adjusted as biases are seen as constants



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# File 'lib/newral/networks/sigmoid.rb', line 25

def delta_rule_hidden( output: nil, expected: nil, weights_at_output_nodes: nil )
  error_delta = []
  @inputs.each do |input|
    d_e_total_d_out = 0
    output.each_with_index do |result,idx|
      d_e_total_d_out_idx = -( expected[idx]-result )
      d_e_out_d_net = (1-result)*result
      d_e_total_d_out_idx = d_e_total_d_out_idx*d_e_out_d_net*weights_at_output_nodes[idx]
      d_e_total_d_out = d_e_total_d_out+d_e_total_d_out_idx
    end
    d_out_d_net = (1-@last_output)*@last_output
    error_delta << d_e_total_d_out*d_out_d_net*calculate_input( input )
  end
  error_delta
end

#output ⇒ Object 



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# File 'lib/newral/networks/sigmoid.rb', line 5

def output
  value = calculate_value
  @last_output =  1/(1+Math.exp(value*-1))
end