This is not a duplicate of the Activation functions for autoencoder performing regression because there is a comment that somebody found a linear activation function but:
- they never said what it was.
- I'm looking for a linear ouput activation function that can also output negative numbers that are less than -1
I am building an autoencoder for feature reduction and have standardized my data because I have many features with different scales. However, this has caused problems because my output activation function (tanh) only outputs between 1 and -1; while some of my inputs are outside of this range. Does anybody know of any other activation function that will output numbers greater than 1 and -1 so my loss function can work with better inputs and outputs?
I have already tried min max norm to get between 0 and 1, and using a sigmoid function. But like I said, I'm working with many features with different scales and would like to see if I can get better results with standardization.
I guess what I'm specifically looking for is a output activation function that is linear; which I've never even heard of.
Anybody?