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Getting best fitting model when using trainlm

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I am running a script which uses the 'trainlm' neural net training algorithm multiple times. It time that it runs it stops when it has not improved for 7 epochs. It then, it seems, provides the model for that last epoch (epoch 'n'), not the best fitting model from epoch n-7, which often is substantially better. Is this correct and is there any way to get the model from the best fitting epoch?

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Accepted Answer

Greg Heath
Greg Heath on 2 Jun 2018
Edited: Greg Heath on 2 Jun 2018
Early stopping ONLY depends on the 15% validation subset performance. NOT on the 70% training or 15% testing performance.
Increasing val set error is proof that the net is not generalizing well to nontraining data.
Since the decreasing improvement neither refers to the 70% training or 15% testing subset, there is no proof that there is a need to back up.
Hope this helps.
Thank you for formally accepting my answer
Greg

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Walter Johnson
Walter Johnson on 3 Jun 2018
Thanks Greg. That is clear and should have been obvious.

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R2018a