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Degreeoffreedom adjustments for classification error?
Posted:
Sep 7, 2013 12:52 PM


http://en.wikipedia.org/wiki/Adjusted_Rsquared
I have been using the estimation degrees of freedom expression
Ndof = Ntrneq  Nw
for mitigating the bias in the MSE estimate of nonlinear neural network regression models when the training data is used for the estimate.
Ntrn  Number of input/target training example vector pairs
O  Dimensionality of the target/output vectors
Ntrneq  Number of scalar training equations: Ntrneq = Ntrn*O
Nw  Number of unknown weights that have to be estimated
SSEtrn  Sumsquarederror
MSEtrn  Biased meansquarederror estimate: MSEtrn = SSEtrn/Ntrneq
MSEtrna  Adjusted meansquarederror estimate: MSEtrna = SSEtrn/Ndof
My question is: Is there a similar adjustment for classifiers?
PctErr = 100*Ntrnerr/Ntrneq
PctErra = 100*Ntrnerr/Ndof ????
TIA,
Greg



