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Feature interaction in subspace clustering using the Choquet integral
The University of New South Wales, Canberra, ACT 2600, Australia.
The University of New South Wales, Canberra, ACT 2600, Australia.ORCID iD: 0000-0002-4255-5130
The University of New South Wales, Canberra, ACT 2600, Australia.
2012 (English)In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 45, no 7, p. 2645-2660Article in journal (Refereed) Published
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Abstract [en]

Subspace clustering has recently emerged as a popular approach to removing irrelevant and redundant features during the clustering process. However, most subspace clustering methods do not consider the interaction between the features. This unawareness limits the analysis performance in many pattern recognition problems. In this paper, we propose a novel subspace clustering technique by introducing the feature interaction using the concepts of fuzzy measures and the Choquet integral. This new framework of subspace clustering can provide optimal subsets of interacted features chosen for each cluster, and hence can improve clustering-based pattern recognition tasks. Various experimental results illustrate the effective performance of the proposed method.

Place, publisher, year, edition, pages
Elsevier, 2012. Vol. 45, no 7, p. 2645-2660
Keyword [en]
Subspace clustering; Fuzzy clustering; Choquet integral; Fuzzy measure; Feature interaction; Pattern recognition
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-127902DOI: 10.1016/j.patcog.2012.01.019ISI: 000302451000017Scopus ID: 2-s2.0-84857999603OAI: oai:DiVA.org:liu-127902DiVA: diva2:928498
Available from: 2016-05-16 Created: 2016-05-13 Last updated: 2018-01-10Bibliographically approved

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Pham, Tuan D

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