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ICDAR
2003
IEEE
14 years 3 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 9 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 11 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 9 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 11 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...