Can we say that overfitting occur in this plot?
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Performance plot from ANN is obtained as shown below.Does overfitting happen here?
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Greg Heath
am 23 Aug. 2018
This is a case of
*OVERTRAINING AN OVERFIT NET*
There are at least 3 ways to avoid this:
1. *DO NOT OVERFIT:*
Make sure that the number of unknown weights, Nw does not
exceed the number of training equations, Ntrneq.
2. *DO NOT OVERTRAIN*
In particular, the problem is not necessarily the
overfitting. Overfitting is easily mitigated by NOT
OVERTRAINING
a. Use a VALIDATION set to implement "EARLY STOPPING".
b. Use "REGULARIZATION" via TRAINBR to implement
"BAYESIAN RREGULARIZATION"
See
https://www.mathworks.com/matlabcentral/answers/280818-how-to-solve-overtrained-nn-with-validation-stop
Hope this helps.
Thank you for formally accepting my answer
Greg
4 Kommentare
KAE
am 5 Sep. 2018
Bearbeitet: KAE
am 5 Sep. 2018
And in the first plot (original question), the val error rate only increases for 5 continuous epochs, during epoch 6-11, while the training error is decreasing. Since 5 is less than the default of 6, the first plot shows overtraining. Is this interpretation right?
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