Title :
Classification with nonexclusive patterns
Author :
Chang, Inhao ; Loew, Murray
Author_Institution :
CyberCash Inc., Reston, VA, USA
Abstract :
In this paper, classification problems with N non-mutually exclusive classes are discussed. We introduce a method which can systematically formulate 2n mutually exclusive classes without additional training data. We also show that the error rate of the new method is lower than that of the traditional approach when patterns are not mutually exclusive
Keywords :
pattern classification; probability; set theory; statistical analysis; error rate; nonexclusive pattern classification; probability; set theory; statistical descriptions; Computer science; Diseases; Error analysis; Error probability; Marine vehicles; Pattern recognition; Training data;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.546735