Survey of Multiobjective Evolutionary Algorithms for Data Mining: Part II

This paper is the second part of a two-part paper, which is a survey of multiobjective evolutionary algorithms for data mining problems. In Part I , multiobjective evolutionary algorithms used for feature selection and classification have been reviewed. In this part, different multiobjective evoluti...

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Published in:IEEE transactions on evolutionary computation Vol. 18; no. 1; pp. 20 - 35
Main Authors: Mukhopadhyay, Anirban, Maulik, Ujjwal, Bandyopadhyay, Sanghamitra, Coello, Carlos A. Coello
Format: Journal Article
Language:English
Published: New York IEEE 01.02.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1089-778X, 1941-0026
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Abstract This paper is the second part of a two-part paper, which is a survey of multiobjective evolutionary algorithms for data mining problems. In Part I , multiobjective evolutionary algorithms used for feature selection and classification have been reviewed. In this part, different multiobjective evolutionary algorithms used for clustering, association rule mining, and other data mining tasks are surveyed. Moreover, a general discussion is provided along with scopes for future research in the domain of multiobjective evolutionary algorithms for data mining.
AbstractList This paper is the second part of a two-part paper, which is a survey of multiobjective evolutionary algorithms for data mining problems. In Part I , multiobjective evolutionary algorithms used for feature selection and classification have been reviewed. In this part, different multiobjective evolutionary algorithms used for clustering, association rule mining, and other data mining tasks are surveyed. Moreover, a general discussion is provided along with scopes for future research in the domain of multiobjective evolutionary algorithms for data mining.
This paper is the second part of a two-part paper, which is a survey of multiobjective evolutionary algorithms for data mining problems. In Part I [Ref 1] , multiobjective evolutionary algorithms used for feature selection and classification have been reviewed. In this part, different multiobjective evolutionary algorithms used for clustering, association rule mining, and other data mining tasks are surveyed. Moreover, a general discussion is provided along with scopes for future research in the domain of multiobjective evolutionary algorithms for data mining.
Author Maulik, Ujjwal
Mukhopadhyay, Anirban
Bandyopadhyay, Sanghamitra
Coello, Carlos A. Coello
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  givenname: Sanghamitra
  surname: Bandyopadhyay
  fullname: Bandyopadhyay, Sanghamitra
  email: sanghami@isical.ac.in
  organization: Machine Intell. Unit, Indian Stat. Inst., Kolkata, India
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  givenname: Carlos A. Coello
  surname: Coello
  fullname: Coello, Carlos A. Coello
  email: ccoello@cs.cinvestav.mx
  organization: Dept. de Comput. (Evolutionary Comput. Group), CINVESTAV-IPN, Mexico City, Mexico
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Snippet This paper is the second part of a two-part paper, which is a survey of multiobjective evolutionary algorithms for data mining problems. In Part I ,...
This paper is the second part of a two-part paper, which is a survey of multiobjective evolutionary algorithms for data mining problems. In Part I [Ref 1] ,...
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SubjectTerms Association rule mining
Association rules
biclustering
Biological cells
Classification
Clustering
Clustering algorithms
Data mining
Encoding
ensemble learning
Evolutionary algorithms
Indexes
Linear programming
multiobjective evolutionary algorithms
Tasks
Title Survey of Multiobjective Evolutionary Algorithms for Data Mining: Part II
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https://www.proquest.com/docview/1520945567
Volume 18
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