In order to understand what kinds of errors a network is making, or in the case where a network can produce multiple outputs for a given input, it is useful to be able to compare the actual output the network came up with against all of the possible training events to find the one that matches the closest. The ClosestEventStat does exactly that.
The closest event stat reports both the distance in the dist
field, and the name of the event which was closest to the current output
pattern in the ev_nm
field. If the ev_nm
matches that of
the currently presented event (cur_event
of the TrialProcess),
then sm_nm
is 1, else it is 0. The average of this value gives a
"percent correct" measure for forced-choice performance among the
different items in the environment. The distance can be computed in
several different ways, as described below:
CompareType cmp_type
SUM_SQUARES
EUCLIDIAN
HAMMING_DIST
COVAR
CORREL
INNER_PROD
CROSS_ENTROPY
float dist_tol
bool norm
INNER_PROD
is being taken, this will result in a normalized
inner-product measure (dividing by the magnitudes of the individual
weight vectors).