In a FeedForward NNet, what exactly is one iteration?

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Sam Speake
Sam Speake 2018-5-23
评论： Greg Heath 2018-5-25
When you train a feedforward neural net with no changes, you see a GUI which includes "Epoch: 0 [ x iterations ] 1000" Does the x value represent the amount of pieces of data that were passed (such as 1 image from a data set of images), or does it represent a full pass of the entire data set?

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Majid Farzaneh
Majid Farzaneh 2018-5-24
Hello, In every neural network there is an optimization algorithm to set optimum weights and biases; and optimization algorithms are usually iterative. 1 epoch means one iteration in the optimization algorithm.
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Majid Farzaneh
Majid Farzaneh 2018-5-24
Yes, that's true. In every change for weights, network needs to calculate MSE and for MSE it needs to classify all training data with new weights.
Greg Heath
Greg Heath 2018-5-25
Optimization algorithms TRY to optimize the goal. Many/most times they do not achieve the goal.
Nevertheless, they are often considered successful if they just get close enough.
For example, I often design neural networks to yield an output target t, given an input function x.
I take as a reference output
yref = mean(t')
the corresponding mean square error is
MSEref = mean(var(t',1))
My training goal is typically
MSEgoal = 0.01*MSEref
which preserves 99% of the target variance,

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