Sequence of layers of this network
All weights of layers
Compute output of neural network with given input If drop-out is used, to average drop-out effect, we need to multiply output by presence probability.
Compute output of neural network with given input If drop-out is used, to average drop-out effect, we need to multiply output by presence probability.
an input vector
output of the vector
All accumulated delta weights of layers
All accumulated delta weights of layers
all accumulated delta weights
Collected input & output of each layer
Collected input & output of each layer
Forward computation for training.
Forward computation for training. If drop-out is used, we need to drop-out entry of input vector.
input matrix
output matrix
Sequence of layers of this network
Sugar: Forward computation for validation.
Sugar: Forward computation for validation. Calls apply(x)
input matrix
output matrix
Serialize network to JSON
Backpropagation algorithm
Backpropagation algorithm
backpropagated error from error function
Network: A basic network implementation