Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6653
Title: Ensemble of Multi-Objective Clustering Unified With H-Confidence Metric as Validity Metric
Authors: Sert, Onur Can
Dursun, Kayhan
Özyer, Tansel
Keywords: Multi-Objective Clustering
NSGA-II
h-confidence
Issue Date: 2011
Publisher: IEEE Computer Soc
Source: International Conference on Advances in Social Networks Analysis and Mining (ASONAM) -- JUL 25-27, 2011 -- Kaohsiung, TAIWAN
Abstract: Multi objective clustering is one focused area of multi objective optimization. Multi objective optimization attracted many researchers in several areas over a decade. Utilizing multi objective clustering mainly considers multiple objectives simultaneously and results with several natural clustering solutions. Obtained result set suggests different point of views for solving the clustering problem. This paper assumes all potential solutions belong to different experts and in overall; ensemble of solutions finally has been utilized for finding the final natural clustering. We have tested on categorical, further on mixed credit card dataset with different objectives, and compared them against single objective clustering result in terms of purity.
URI: https://doi.org/10.1109/ASONAM.2011.95
https://hdl.handle.net/20.500.11851/6653
ISBN: 978-0-7695-4375-8
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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