article

Building ensemble classifiers using belief functions and OWA operators

Authors:

Marek Reformat,

Ronald R. YagerAuthors Info & Claims

Soft Computing - A Fusion of Foundations, Methodologies and Applications, Volume 12, Issue 6

Pages 543 - 558

Published: 01 April 2008 Publication History

Abstract

A pervasive task in many forms of human activity is classification. Recent interest in the classification process has focused on ensemble classifier systems. These types of systems are based on a paradigm of combining the outputs of a number of individual classifiers. In this paper we propose a new approach for obtaining the final output of ensemble classifiers. The method presented here uses the Dempster---Shafer concept of belief functions to represent the confidence in the outputs of the individual classifiers. The combing of the outputs of the individual classifiers is based on an aggregation process which can be seen as a fusion of the Dempster rule of combination with a generalized form of OWA operator. The use of the OWA operator provides an added degree of flexibility in expressing the way the aggregation of the individual classifiers is performed.

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Cited By

Yu DPan TXu ZYager R(2023)Exploring the knowledge diffusion and research front of OWA operator: a main path analysisArtificial Intelligence Review10.1007/s10462-023-10462-y56:10(12233-12255)Online publication date: 16-May-2023
https://dl.acm.org/doi/10.1007/s10462-023-10462-y
Rakesh DAnwit RJana P(2023)A new ranking-based stability measure for feature selection algorithmsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-022-07767-527:9(5377-5396)Online publication date: 3-Jan-2023
https://dl.acm.org/doi/10.1007/s00500-022-07767-5
Tajoddin AAbadi M(2019)RAMDApplied Intelligence10.1007/s10489-018-01405-049:7(2641-2658)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s10489-018-01405-0
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Index Terms

Building ensemble classifiers using belief functions and OWA operators
1. Computing methodologies

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cover image Soft Computing - A Fusion of Foundations, Methodologies and Applications

Soft Computing - A Fusion of Foundations, Methodologies and Applications Volume 12, Issue 6

April 2008

92 pages

ISSN:1432-7643

EISSN:1433-7479

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Copyright © Copyright © 2008 Springer-Verlag.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 April 2008

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Cited By

Yu DPan TXu ZYager R(2023)Exploring the knowledge diffusion and research front of OWA operator: a main path analysisArtificial Intelligence Review10.1007/s10462-023-10462-y56:10(12233-12255)Online publication date: 16-May-2023
https://dl.acm.org/doi/10.1007/s10462-023-10462-y
Rakesh DAnwit RJana P(2023)A new ranking-based stability measure for feature selection algorithmsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-022-07767-527:9(5377-5396)Online publication date: 3-Jan-2023
https://dl.acm.org/doi/10.1007/s00500-022-07767-5
Tajoddin AAbadi M(2019)RAMDApplied Intelligence10.1007/s10489-018-01405-049:7(2641-2658)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s10489-018-01405-0
Su XLi LQian HMahadevan SDeng Y(2019)A new rule to combine dependent bodies of evidenceSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-03804-y23:20(9793-9799)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1007/s00500-019-03804-y
Trabelsi AElouedi ZLefevre E(2017)Comparing dependent combination rules under the belief classifier fusion frameworkSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-016-2402-921:23(6919-6932)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1007/s00500-016-2402-9
Jiang WWei BZhan JXie CZhou D(2016)A visibility graph power averaging aggregation operatorComputers and Industrial Engineering10.1016/j.cie.2016.09.009101:C(260-268)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1016/j.cie.2016.09.009
Parhizkar EAbadi M(2015)BeeOWANeurocomputing10.1016/j.neucom.2015.03.051166:C(367-381)Online publication date: 20-Oct-2015
https://dl.acm.org/doi/10.1016/j.neucom.2015.03.051
Quost BDenœux T(2009)Learning from data with uncertain labels by boosting credal classifiersProceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data10.1145/1610555.1610561(38-47)Online publication date: 28-Jun-2009
https://dl.acm.org/doi/10.1145/1610555.1610561

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