An Experimental Study of the Optimal Class-Selective Rejection Rule
نویسنده
چکیده
This report reviews various class-selective rejection rules for pattern recognition. A rejection rule is called class-selective if it does not reject an ambiguous pattern from all classes but only from those classes that are most unlikely to issue the pattern. Both optimal and suboptimal rules, e.g. top-n ranking, are considered. Experimental comparisons performed on the recognition of isolated numerals from the NIST databases show that the optimal classselective rejection rule is actually better than two other heuristic rules. CR
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