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Fuzzy mixed-prototype clustering algorithm for microarray data analysis
School of Computer Science, China University of Mining and Technology, Xuzhou, Jiangsu, China.
Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-4255-5130
Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong.
School of Computer Science, China University of Mining and Technology, Xuzhou, Jiangsu, China.
2018 (engelsk)Inngår i: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 276, s. 42-54Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Being motivated by combining the advantages of hyperplane-based pattern analysis and fuzzy clustering techniques, we present in this paper a fuzzy mix-prototype (FMP) clustering for microarray data analysis. By integrating spherical and hyper-planar cluster prototypes, the FMP is capable of capturing latent data models with both spherical and non-spherical geometric structures. Our contributions of the paper can be summarized into three folds: first, the objective function of the FMP is formulated. Second, an iterative solution which minimizes the objective function under given constraints is derived. Third, the effectiveness of the proposed FMP is demonstrated through experiments on yeast and leukemia data sets.

sted, utgiver, år, opplag, sider
Elsevier, 2018. Vol. 276, s. 42-54
Emneord [en]
FMP, Microarray data analysis, Fuzzy clustering
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-141163DOI: 10.1016/j.neucom.2017.06.083ISI: 000419222000005OAI: oai:DiVA.org:liu-141163DiVA, id: diva2:1144031
Tilgjengelig fra: 2017-09-25 Laget: 2017-09-25 Sist oppdatert: 2018-01-22bibliografisk kontrollert

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