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Well, that's the easiest way I can think of... And it really surprised me that the standard deviation is almost the same for most bots. If so, then I think normalising standard deviation may not be that useful — since we already tune weights very hard. But for neural networks, I think this is invaluable, since we don't tune weights manually, and that would affect the learning speed a lot.

I never thought about normalizing standard deviation for neural networks, because they should adjust themselves to the attributes anyways. But yeah, the learning speed is probably affected by it, I should consider that for further NN experiments :D