DocumentCode :
3021563
Title :
A topology based multi-classifier system
Author :
Prudent, Yann ; Ennaji, Abdellatif
Author_Institution :
PSI Lab., France
fYear :
2005
fDate :
29 Aug.-1 Sept. 2005
Firstpage :
670
Abstract :
This paper introduces a new scheme for the general problem of classification task-solving by designing a multi-classifier system. The distribution process respects the data topology in the feature space in order to reach reliable decisions. To this end we use a self-organizing network which gives a graph that represents the data topology. During the decision process this graph is used to activate the appropriate classifiers among a set of committee experts. Comparative results are given for a handwritten digit recognition problem.
Keywords :
graph theory; pattern classification; self-organising feature maps; classification task solving; data topology; handwritten digit recognition; multiclassifier system; self-organizing network; Handwriting recognition; Laboratories; Machine learning; Network topology; Neural networks; Pattern recognition; Self-organizing networks; Support vector machine classification; Support vector machines; Text analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
ISSN :
1520-5263
Print_ISBN :
0-7695-2420-6
Type :
conf
DOI :
10.1109/ICDAR.2005.37
Filename :
1575629
Link To Document :
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