Are there features that the input and target values should follow before training in a neural network?
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Even with normalization or mapping in a range [-1,1] before training, I have seen that a good scaling of the data may improve the performance of the neural network. How to define a good scaling for both the input and output data when the range is very large?
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Accepted Answer
Greg Heath
on 28 Nov 2015
You are creating a problem that doesn't exist.
Pretraining standardization can be used to eliminate or modify outliers. Then you can use either or both standardization and/or normalization.
Hope this helps.
Thank you for formally accepting my answer
Greg
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