Feature interaction in subspace clustering using the Choquet integral
2012 (English)In: Pattern Recognition, ISSN 0031-3203, Vol. 45, no 7, 2645-2660 p.Article in journal (Refereed) PublishedText
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
2012. Vol. 45, no 7, 2645-2660 p.
Subspace clustering; Fuzzy clustering; Choquet integral; Fuzzy measure; Feature interaction; Pattern recognition
IdentifiersURN: urn:nbn:se:liu:diva-127902DOI: 10.1016/j.patcog.2012.01.019OAI: oai:DiVA.org:liu-127902DiVA: diva2:928498