Keras Neural Network. Preprocessing

I have this doubt when I fit a neural network in a regression problem. I preprocessed the predictors (features) of my train and test data using the methods of Imputers and Scale fr

Solution 1:

Usually, if you are doing regression you should use a linear' activation in the last layer. A sigmoid function will 'favor' values closer to 0 and 1, so it would be harder for your model to output intermediate values.

If the distribution of your targets is gaussian or uniform I would go with a linear output layer. De-processing shouldn't be necessary unless you have very large targets.