Is normalization necessary for input and output data in an Artificial Neural Network (ANN)? Does it impact the network's performance?

Is normalization necessary for input and output data in an Artificial Neural Network (ANN)? Does it impact the network's performance?

[Mohammed]

Yes , the input and the output nessecary to export them in workspace this stap is important , and of course you should remembre the lenght of your inputs and outputs is the same lenght to plot the graph normally

if you want to see my project about ANN you can go and check my repository in github:

https://github.com/moha999DJ/ANN

[Sunita]

, first we normalize the data >>>>> export to to workplace>>>> run the ANN >>> de-normalise the output . is that correct?

Answer 1

[Walter Roberson]

Is normalization necessary for input and output data in an Artificial Neural Network (ANN)

No, it is not necessary.

Does it impact the network's performance?

Yes, it does affect network's performance.

When features are to different scales, then methods such as gradient descent tend to favour the features unequally. This results in effectively weighting some features differently than others. If you are considering each feature as having value relative only to itself, then you need to normalize in order to be fair. If, though, the values have meaning between features, then you do not always want to rescale.