A dynamic model of classifier competence based on the local fuzzy confusion matrix and the random reference classifier - Digital Library of Zielona Góra

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A dynamic model of classifier competence based on the local fuzzy confusion matrix and the random reference classifier

Title: A dynamic model of classifier competence based on the local fuzzy confusion matrix and the random reference classifier

Creator:

Trajdos, Pawel ; Kurzynski, Marek

Resource Type:

Contributor:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Group publication title:

AMCS, Volume 26 (2016)

Abstract:

Nowadays, multiclassifier systems (MCSs) are being widely applied in various machine learning problems and in many different domains. Over the last two decades, a variety of ensemble systems have been developed, but there is still room for improvement. This paper focuses on developing competence and interclass cross-competence measures which can be applied as a method for classifiers combination. ; The cross-competence measure allows an ensemble to harness pieces of information obtained from incompetent classifiers instead of removing them from the ensemble. The cross-competence measure originally determined on the basis of a validation set (static mode) can be further easily updated using additional feedback information on correct/incorrect classification during the recognition process (dynamic mode). The analysis of computational and storage complexity of the proposed method is presented. ; The performance of the MCS with the proposed cross-competence function was experimentally compared against five reference MCSs and one reference MCS for static and dynamic modes, respectively. Results for the static mode show that the proposed technique is comparable with the reference methods in terms of classification accuracy. For the dynamic mode, the system developed achieves the highest classification accuracy, demonstrating the potential of the MCS for practical applications when feedback information is available.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Resource Identifier:

oai:zbc.uz.zgora.pl:79122

DOI:

10.1515/amcs-2016-0012

Pages:

Source:

AMCS, volume 26, number 1 (2016) ; click here to follow the link

Language:

Rights:

Biblioteka Uniwersytetu Zielonogórskiego

Subject and keywords:

multiclassifier cross-competence measure confusion matrix feedback information

Object collections:

Digital Library of Zielona Góra > Repository > Faculties > Faculty of Computer, Electrical and Control Engineering

Digital Library of Zielona Góra > Repository > Types of work > Articles

Digital Library of Zielona Góra > Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2016)

Last modified:

Nov 5, 2024

In our library since:

May 9, 2024

Number of object content hits:

29

All available object's versions:

https://zbc.uz.zgora.pl/publication/88949

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Show description in OAI-PMH format:

International Journal of Applied Mathematics and Computer Science (AMCS)

Edition name	Date
A dynamic model of classifier competence based on the local fuzzy confusion matrix and the random reference classifier	Nov 5, 2024

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