Assertion: neural network's output | /r/HasProperty | calculated
Facets:
value: similarly
type: DEGREE
value: by performing this procedure
type: MANNER
value: as below
type: OTHER
Source sentences:
text: The output can be calculated by applying the activation function over the net input.
text: The output of the i+1th layer can be calculated as:
text: Similarly, the output from other hidden node can be calculated.
text: Then output V from the node in consideration can be calculated as below (f is an activation function such as sigmoid):
text: Similarly, outputs from the other node in the hidden layer is also calculated.
text: Forward pass: the outputs are calculated and the error at the output units calculated.
text: The signal flows from left to right, and the final output is calculated by performing this procedure for all the nodes.
text: The output is compared with desired output and error is calculated using cost function.