I'm working on a pet project, feeding lots of data into a neural net. My neural net results (how fast the net trains) might be (positively!) affected by using a transformative function. What I'm trying to do is to "separate" the values apart so that one value is easier for the neural network to discriminate the values while training. In my uneducated attempts this seems like a "kernel" method (forcing values into higher dimensions for better network value discrimination). One of the common functions I found is tanh. The Wolfram site had a definition of tanh using e (exp) so I wrote my own tanh for experimentation. Currently I'm not using tanh, I'm just squaring the calculated values before the values are fed to the neural network.
What other functions might be transformative functions?
TIA
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