"Suresh" wrote in message <firstname.lastname@example.org>... > How to decide the value of Error goal while training a neural network for different pattern recognition problems ?
Unfortunately, there is no analytic relationship between the discontinuous classification error rate Nerr/N and continuous error (target-output). Therefore, classifiers are usually trained to minimize the continuous mean-squared-error even though low classification error rate is the ultimate goal.
Subsequently, the same rule is used for regression with O-dimensional targets and classification with O = c classes where the target matrix contains columns of the c-dimensional unit matrix eye(c). In each case the data provides Neq equations
Neq = N*O
to estimate Nw unknown weights. The resulting estimation degree-of-freedom is
Ndof = Neq-Nw
The NAIVE MODEL assumes that the output is a constant equal to the mean of the target values