I use the training function "traingd" to train a shallow neural network:
trainedNet = train(net,X,T)
For the training function "traingd": How is the parameter minimum performance gradient (net.trainParam.min_grad) defined?
As the gradient for the gradient descent is usually a vector, but net.trainParam.min_grad is a scalar value, I am confused.
Is it the change in the performace (loss) between 2 iterations, and if yes: Does it refer to the training, validation or testing errror?
Thanks in advance!
I use MATLAB 2013 and 2015 with the neural network toolbox.