DocumentCode :
384265
Title :
A supervised classification scheme using positive Boolean function
Author :
Han, Chin-Chuan
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Chung-Hua Univ., Hsinchu, Taiwan
Volume :
2
fYear :
2002
fDate :
2002
Firstpage :
100
Abstract :
In this paper, a classifier based on the positive Boolean function (PBF) is proposed for the supervised pattern classification. A PBF is exactly represented as one sum-of-product form without any negative components. The PBF possesses the well-known threshold decomposition and stacking properties. The classification errors can be calculated from the summation of the absolute errors incurred at each level. The optimal PBF are found and designed to be a classifier by minimizing the classification error rate along the training samples. The experimental results were given to show the validity of our proposed approaches.
Keywords :
Boolean functions; minimisation; pattern classification; PBF; absolute errors; classification error rate minimization; positive Boolean function; stacking; sum-of-product form; supervised pattern classification; threshold decomposition; Boolean functions; Computer science; Digital filters; Electronic mail; Error analysis; Image edge detection; Pattern classification; Pattern recognition; Signal processing; Stacking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-1695-X
Type :
conf
DOI :
10.1109/ICPR.2002.1048247
Filename :
1048247
Link To Document :
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