Abstract:
A vectorial criterion of recognition performance is proposed; an algorithm is obtained which maximizes simultaneously all conditional probabilities of making correct decisions with upper bound probabilities of making erroneous decisions. Unlike the Bayesian algorithm this one does not require knowledge of the a priori probability distribution on a set of classes and quatitative descriptions of payoffs for making different decisions.
Fulltext:
PDF file (1098 kB)