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Harmonious Genetic Clustering
Huang, Faliang1; Li, Xuelong2; Zhang, Shichao3,4; Zhang, Jilian5
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To automatically determine the number of clusters and generate more quality clusters while clustering data samples, we propose a harmonious genetic clustering algorithm, named HGCA, which is based on harmonious mating in eugenic theory. Different from extant genetic clustering methods that only use fitness, HGCA aims to select the most suitable mate for each chromosome and takes into account chromosomes gender, age, and fitness when computing mating attractiveness. To avoid illegal mating, we design three mating prohibition schemes, i.e., no mating prohibition, mating prohibition based on lineal relativeness, and mating prohibition based on collateral relativeness, and three mating strategies, i.e., greedy eugenics-based mating strategy, eugenics-based mating strategy based on weighted bipartite matching, and eugenics-based mating strategy based on unweighted bipartite matching, for harmonious mating. In particular, a novel single-point crossover operator called variable-length-and-gender-balance crossover is devised to probabilistically guarantee the balance between population gender ratio and dynamics of chromosome lengths. We evaluate the proposed approach on real-life and artificial datasets, and the results show that our algorithm outperforms existing genetic clustering methods in terms of robustness, efficiency, and effectiveness.

KeywordData Clustering Eugenic Theory Genetic Clustering Mating Operator
Indexed BySCI ; EI
WOS IDWOS:000418291400017
EI Accession Number20170403279606
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Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Fujian Normal Univ, Fac Software, Fujian Engn Res Ctr Publ Serv Big Data Min & Appl, Fuzhou 350007, Fujian, Peoples R China;
2.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt Imagery Anal & Learning, Xian 710119, Shaanxi, Peoples R China;
3.Guangxi Normal Univ, Guangxi Key Lab MIMS, Guilin 541004, Peoples R China;
4.Guangxi Normal Univ, Coll Comp Sci & Informat Technol, Guilin 541004, Peoples R China;
5.Guangxi Univ Finance & Econ, Guangxi Key Lab Cross Border E Commerce Intellige, Nanning 530003, Peoples R China
Recommended Citation
GB/T 7714
Huang, Faliang,Li, Xuelong,Zhang, Shichao,et al. Harmonious Genetic Clustering[J]. IEEE TRANSACTIONS ON CYBERNETICS,2018,48(1):199-214.
APA Huang, Faliang,Li, Xuelong,Zhang, Shichao,&Zhang, Jilian.(2018).Harmonious Genetic Clustering.IEEE TRANSACTIONS ON CYBERNETICS,48(1),199-214.
MLA Huang, Faliang,et al."Harmonious Genetic Clustering".IEEE TRANSACTIONS ON CYBERNETICS 48.1(2018):199-214.
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