Function approximation but not with MLP. What can I use to get good results?
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Good result means: less than 18 MSE (mean squared error).
I've got an X matrix: 10000x9 (10000 rows, 9 dimensional input) I've got an Y matrix: 10000x1 (10000 rows, 1 dimensional output)
I tried to use MLP but I couldn't get less than 21 MSE.
So what else can I use for a function approximation problem?
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