__init__ (
        self,
        num_nodes,
        activation=logistic_function,
        )

Initialize the Output Layer.

Arguments:

• num_nodes -- The number of nodes in this layer. This corresponds to the number of outputs in the neural network.

• activation -- The transformation function used to transform predicted values.

backpropagate (
        self,
        outputs,
        learning_rate,
        momentum,
        )

Calculate the backpropagation error at a given node.

This calculates the error term using the formula:

p = (z - t) z (1 - z)

where z is the calculated value for the node, and t is the real value.

Arguments:

• outputs - The list of output values we use to calculate the errors in our predictions.

get_error (
        self,
        real_value,
        node_number,
        )

Return the error value at a particular node.

update ( self,  previous_layer )

Update the value of output nodes from the previous layers.

Arguments:

• previous_layer -- The hidden layer preceeding this.