Constructing error correcting output coding classifiers

Author

Yamaguchi, Nobuhiko ; Ishii, Naohiro

Author_Institution

Dept. of Intelligence & Comput. Sci., Nagoya Inst. of Technol., Japan

Volume

5

fYear

2002

fDate

18-22 Nov. 2002

Firstpage

2635

Abstract

The topic of this paper is a special family of classifiers known as error correcting output coding (ECOC) classifiers. These are one of ensemble methods which prepare redundant discriminant functions and then construct a classifier by combining these discriminant functions. We focus on a method for combining the discriminant functions and develop a extension of the ECOC classifiers. Experiments on artificial data demonstrate that a much better performance can be obtained by the new classifier.

Keywords

Bayes methods; decoding; error correction codes; error statistics; least squares approximations; pattern classification; Bayes classifiers; K-class pattern classification problems; artificial data; code matrix; codeword prediction; combination strategy; decoding method; ensemble methods; error correcting codes; error correcting output coding classifiers; least squares; posterior probabilities; reduced error probability; redundant discriminant functions; Computer errors; Computer science; Decoding; Error correction; Error correction codes; Error probability;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on

Print_ISBN

981-04-7524-1

Type

conf

DOI

10.1109/ICONIP.2002.1201973

Filename

1201973