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ICDAR
2003
IEEE
13 years 10 months ago
A Multiclass Classification Method Based on Multiple Pairwise Classifiers
In this paper, a new method of composing a multiclass classifier using pairwise classifiers is proposed. A “Resemblance Model” is exploited to calculate a posteriori probabili...
Tomoyuki Hamamura, Hiroyuki Mizutani, Bunpei Irie
NPL
2008
100views more  NPL 2008»
13 years 4 months ago
Comparing Combination Rules of Pairwise Neural Networks Classifiers
A decomposition approach to multiclass classification problems consists in decomposing a multiclass problem into a set of binary ones. Decomposition splits the complete multiclass ...
Olivier Lezoray, Hubert Cardot
ACCV
2006
Springer
13 years 6 months ago
Learning Multi-category Classification in Bayesian Framework
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
Atul Kanaujia, Dimitris N. Metaxas
PR
2008
154views more  PR 2008»
13 years 4 months ago
Data-driven decomposition for multi-class classification
This paper presents a new study on a method of designing a multi-class classifier: Data-driven Error Correcting Output Coding (DECOC). DECOC is based on the principle of Error Cor...
Jie Zhou, Hanchuan Peng, Ching Y. Suen
ICPR
2004
IEEE
14 years 5 months ago
Multi-Class Extensions of the GLDB Feature Extraction Algorithm for Spectral Data
The Generalized Local Discriminant Bases (GLDB) algorithm proposed by Kumar, Ghosh and Crawford in [4], is a effective feature extraction method for spectral data. It identifies g...
Pavel Paclík, Robert P. W. Duin, Serguei Ve...