The SE_Stat object is a stat that iterates over the units that have
target values in a network, and computes the difference between the
activation and the target value. This is useful for monitoring learning
performance over training. The current value of this statistic can be
found in the se
member. Also, there is a tolerance
parameter which causes absolute differences of less than this amount to
result in zero error. Thus, if one only was interested in whether the
network was on the right side of .5, you would set the tolerance to .5
(assuming a 0 to 1 activation range).
There is also a CE_Stat and a RBpSE_Stat defined in the Bp
version of the executable. These compute the cross-entropy error
statistic and a version of squared-error that takes into account the
dt
parameter of the recurrent backprop algorithm.