An Improved Genetic Clustering Algorithm for Categorical Data

An Improved Genetic Clustering Algorithm for Categorical Data

Deng et al. [Deng, S., He, Z., Xu, X.: G-ANMI: A mutual information based genetic clustering algorithm for categorical data, Knowledge-Based Systems 23, 144–149(2010)] proposed a mutual information based genetic clustering algorithm named G-ANMI for categorical data. While G-ANMI is superior or comp...

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Bibliographic Details
Main Authors: Jasni, Mohamad Zain, Qin, Hongwu, Ma, Xiuqin, Herawan, Tutut
Other Authors: Washio, Takashi
Format: Book Section
Language:English
Published: Springer 2013
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/6186/
http://umpir.ump.edu.my/id/eprint/6186/
http://umpir.ump.edu.my/id/eprint/6186/
http://umpir.ump.edu.my/id/eprint/6186/1/PAKDD13.pdf
id ump-6186
recordtype eprints
spelling ump-61862018-05-21T05:18:21Z http://umpir.ump.edu.my/id/eprint/6186/ An Improved Genetic Clustering Algorithm for Categorical Data Jasni, Mohamad Zain Qin, Hongwu Ma, Xiuqin Herawan, Tutut QA75 Electronic computers. Computer science Deng et al. [Deng, S., He, Z., Xu, X.: G-ANMI: A mutual information based genetic clustering algorithm for categorical data, Knowledge-Based Systems 23, 144–149(2010)] proposed a mutual information based genetic clustering algorithm named G-ANMI for categorical data. While G-ANMI is superior or comparable to existing algorithms for clustering categorical data in terms of clustering accuracy, it is very time-consuming due to the low efficiency of genetic algorithm (GA). In this paper, we propose a new initialization method for G-ANMI to improve its efficiency. Experimental results show that the new method greatly improves the efficiency of G-ANMI as well as produces higher clustering accuracy. Springer Washio, Takashi Luo, Jun 2013 Book Section PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6186/1/PAKDD13.pdf Jasni, Mohamad Zain and Qin, Hongwu and Ma, Xiuqin and Herawan, Tutut (2013) An Improved Genetic Clustering Algorithm for Categorical Data. In: Emerging Trends in Knowledge Discovery and Data Mining: PAKDD 2012 International Workshops: DMHM, GeoDoc, 3Clust, and DSDM, Kuala Lumpur, Malaysia, May 29 – June 1, 2012, Revised Selected Papers. Lecture Notes in Computer Science, 7769 (Lectur). Springer, Berlin Heidelberg, pp. 100-111. ISBN 978-3-642-36778-6 http://dx.doi.org/10.1007/978-3-642-36778-6_9 DOI: 10.1007/978-3-642-36778-6_9
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Jasni, Mohamad Zain
Qin, Hongwu
Ma, Xiuqin
Herawan, Tutut
An Improved Genetic Clustering Algorithm for Categorical Data
description Deng et al. [Deng, S., He, Z., Xu, X.: G-ANMI: A mutual information based genetic clustering algorithm for categorical data, Knowledge-Based Systems 23, 144–149(2010)] proposed a mutual information based genetic clustering algorithm named G-ANMI for categorical data. While G-ANMI is superior or comparable to existing algorithms for clustering categorical data in terms of clustering accuracy, it is very time-consuming due to the low efficiency of genetic algorithm (GA). In this paper, we propose a new initialization method for G-ANMI to improve its efficiency. Experimental results show that the new method greatly improves the efficiency of G-ANMI as well as produces higher clustering accuracy.
author2 Washio, Takashi
author_facet Washio, Takashi
Jasni, Mohamad Zain
Qin, Hongwu
Ma, Xiuqin
Herawan, Tutut
format Book Section
author Jasni, Mohamad Zain
Qin, Hongwu
Ma, Xiuqin
Herawan, Tutut
author_sort Jasni, Mohamad Zain
title An Improved Genetic Clustering Algorithm for Categorical Data
title_short An Improved Genetic Clustering Algorithm for Categorical Data
title_full An Improved Genetic Clustering Algorithm for Categorical Data
title_fullStr An Improved Genetic Clustering Algorithm for Categorical Data
title_full_unstemmed An Improved Genetic Clustering Algorithm for Categorical Data
title_sort improved genetic clustering algorithm for categorical data
publisher Springer
publishDate 2013
url http://umpir.ump.edu.my/id/eprint/6186/
http://umpir.ump.edu.my/id/eprint/6186/
http://umpir.ump.edu.my/id/eprint/6186/
http://umpir.ump.edu.my/id/eprint/6186/1/PAKDD13.pdf
first_indexed 2023-09-18T22:01:45Z
last_indexed 2023-09-18T22:01:45Z
_version_ 1777414444737888256

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