Optimal Decision Functions for Computer Character Recognition
J. T. Chu · Journal of the ACM · 1965
The use of statistical decision functions with computers for character recognition is investigated.The three eases considered are (1) where both the losses due to incorrect decisions and the a priori probability of the characters are known, (2) where the a priori probability is known, but the losses are not, and (3) the reverse of the second ease.For the first ease, Bayes decision functions are reviewed.A theorem about the advantage of using rejection is proved.For the second ease, minimum error and minimum rejection decision functions are defined and obtained.For the third ease, admissible, and a complete class of, decision functions are discussed.Illustrative ex'~mples are given.