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Trying to understand this relationship I came across this conversation in an email group:
I got a problem while analyzing my data using NN. I got R-square with 0.45 with MSE around 5000. SO I am wonder why? There must be a relation between R-square and MSE?
R2 = 1 - SSE/SS0
SSE = N*MSE SS0 = (N-1)*VAR(Target)
VAR(T) = SS0/(N-1) = [SSE/(1-R2)]/(N-1)
~ 5000/0.55 ~ 9091
If you had standardized your targets to unit variance you would have obtained MSE ~ 0.55
Is that correct? What insights can we reach understanding this relationship?