Class: NeuralNetwork::Network

Inherits:
Object
  • Object
show all
Defined in:
lib/neural_network/network.rb

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(layer_sizes) ⇒ Network

Returns a new instance of Network.



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# File 'lib/neural_network/network.rb', line 5

def initialize(layer_sizes)
  @input_layer    = Layer.new(layer_sizes.shift)
  @output_layer   = Layer.new(layer_sizes.pop)
  @hidden_layers  = layer_sizes.map{|layer_size| Layer.new(layer_size)}
  @error          = 0

  connect_layers
end

Instance Attribute Details

#error ⇒ Object

Returns the value of attribute error.



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# File 'lib/neural_network/network.rb', line 3

def error
  @error
end

#hidden_layers ⇒ Object

Returns the value of attribute hidden_layers.



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# File 'lib/neural_network/network.rb', line 3

def hidden_layers
  @hidden_layers
end

#input_layer ⇒ Object

Returns the value of attribute input_layer.



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# File 'lib/neural_network/network.rb', line 3

def input_layer
  @input_layer
end

#output_layer ⇒ Object

Returns the value of attribute output_layer.



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# File 'lib/neural_network/network.rb', line 3

def output_layer
  @output_layer
end

Instance Method Details

#activate(input_values) ⇒ Object 



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# File 'lib/neural_network/network.rb', line 14

def activate(input_values)
  @input_layer.activate(input_values)
  @hidden_layers.each(&:activate)
  @output_layer.activate
end

#train(target_outputs) ⇒ Object

all layers in reverse, back propogate!!



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# File 'lib/neural_network/network.rb', line 21

def train(target_outputs)
  @output_layer.train(target_outputs)

  # set the new network error after training
  @error = error_function(target_outputs)

  @hidden_layers.reverse.each(&:train)
  @input_layer.train
end