CLASS-SELECTIVE REJECTION RULE TO MINIMIZE THE MAXIMUM DISTANCE BETWEEN SELECTED CLASSES

摘要

Class-selective rejection scheme assigns to an input pattern a subset of classes that are most likely to identify the pattern, and not simply reject it. Conventional class-selective rejection rules can minimize the error rate for a given average number of classes. In this paper, an example of unnatural classification is shown by using conventional rules and a new optimum criterion for establishing a class-selective rejection rule is proposed. Its optimality and upper-bound of error rate are proven. Finally, two examples are provided to illustrate various aspects of this optimum decision rule.