Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)

All-Pairs Evolving Fuzzy Classifiers for On-line Multi-Class Classification Problems

Authors
Edwin Lughofer
Corresponding Author
Edwin Lughofer
Available Online August 2011.
DOI
10.2991/eusflat.2011.49How to use a DOI?
Keywords
multi-class problems, all-pairs classification, evolving fuzzy classifiers, preference relation matrix, reliability
Abstract

In this paper, we propose a novel design of evolving fuzzy classifiers in case of multi-class classification problems. Therefore, we exploit the concept of all-pairs aka all-versus-all classification using binary classifiers for each pair of classes, which has some advantages over direct multi-class as well as one-versus-rest classification variants. Regressionbased as well as singleton class label fuzzy classifiers are used as architectures for the binary classifiers, which are evolved and incrementally trained based on the concepts included in the FLEXFIS family (a connection of eVQ and recursive fuzzily weighted least squares). The classification phase considers the preference levels of each pair of classes stored in a preference relation matrix and uses a weighted voting scheme of preference levels, including reliability aspects. The advantage of the new evolving fuzzy classifier concept over single model (using direct multi-class classification concept) and multi model (using one-versus-rest classification concept) architectures will be underlined by empirical evaluations and comparisons at the end of the paper based on high-dimensional real-world multi-class classification problems.

Copyright
© 2011, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)
Series
Advances in Intelligent Systems Research
Publication Date
August 2011
ISBN
978-90-78677-00-0
ISSN
1951-6851
DOI
10.2991/eusflat.2011.49How to use a DOI?
Copyright
© 2011, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Edwin Lughofer
PY  - 2011/08
DA  - 2011/08
TI  - All-Pairs Evolving Fuzzy Classifiers for On-line Multi-Class Classification Problems
BT  - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)
PB  - Atlantis Press
SP  - 372
EP  - 379
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2011.49
DO  - 10.2991/eusflat.2011.49
ID  - Lughofer2011/08
ER  -