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object --+ | AbstractLayer --+ | OutputLayer
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Initialize the Output Layer. Arguments: o num_nodes -- The number of nodes in this layer. This corresponds to the number of outputs in the neural network. o activation -- The transformation function used to transform predicted values.
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Update the value of output nodes from the previous layers. Arguments: o previous_layer -- The hidden layer preceeding this. |
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: o outputs - The list of output values we use to calculate the errors in our predictions. |
Set a weight value from one node to the next. If weights are not explicitly set, they will be initialized to random values to start with.
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Trees | Indices | Help |
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