Package Bio :: Package NeuralNetwork :: Package BackPropagation :: Module Layer :: Class HiddenLayer
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Class HiddenLayer

AbstractLayer --+
                |
               HiddenLayer


Method Summary
  __init__(self, num_nodes, next_layer, activation)
Initialize a hidden layer.
  backpropagate(self, outputs, learning_rate, momentum)
Recalculate all weights based on the last round of prediction.
  update(self, previous_layer)
Update the values of nodes from the previous layer info.
    Inherited from AbstractLayer
  __str__(self)
Debugging output.
  set_weight(self, this_node, next_node, value)
Set a weight value from one node to the next.

Method Details

__init__(self, num_nodes, next_layer, activation=<function logistic_function at 0x1932aa0>)
(Constructor)

Initialize a hidden layer.

Arguments:

o num_nodes -- The number of nodes in this hidden layer.

o next_layer -- The next layer in the neural network that this is connected to.

o activation -- The transformation function used to transform predicted values.
Overrides:
Bio.NeuralNetwork.BackPropagation.Layer.AbstractLayer.__init__

backpropagate(self, outputs, learning_rate, momentum)

Recalculate all weights based on the last round of prediction.

Arguments:

o learning_rate -- The learning rate of the network

o momentum - The amount of weight to place on the previous weight change.

o outputs - The output values we are using to see how good our network is at predicting things.

update(self, previous_layer)

Update the values of nodes from the previous layer info.

Arguments:

o previous_layer -- The previous layer in the network.

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