Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6480
Title: Deciding on number of clusters by multi-objective optimization and validity analysis
Authors: Ozyer, Tansel
Alhajj, Reda
Keywords: CURE
clustering
data mining
genetic algorithm
multi-objective optimization
validity analysis
Issue Date: 2008
Publisher: Old City Publishing Inc
Source: 7th International FLINS Conference on Applied Artificial Intelligence -- AUG 29-31, 2006 -- Genova, ITALY
Abstract: Clustering is unsupervised process that classified a given set of objects into groups. The effectiveness of a clustering approach is mainly judged by its capability of producing clusters by maximizing both: within cluster similarity and between clusters dissimilarity. However, clustering algorithms expect the number of clusters be specified beforehand; this requires domain expertise. In this study, we demonstrate the effectiveness of different validity indices in guiding the process of a clustering approach that automatically determines the number of clusters before starting the actual clustering process. The target is achieved by first running a multi-objective genetic algorithm on a sample of the given dataset to find the set of alternative Solutions for a given range of possible number of clusters. Then, we apply cluster validity indexes to find the most appropriate number of clusters. We decide on running the genetic algorithm on a sample rather than the whole dataset simply because we want to benefit from the power of the genetic algorithm in automatically estimating the number of clusters, without being negatively affected by the poor performance of the genetic algorithm process as the dataset size increases. Finally, we run CURE to do the actual clustering of the whole dataset by feeding the determined number of clusters as input. The reported test results on two datasets demonstrate the applicability, efficiency and effectiveness of the proposed approach.
URI: https://hdl.handle.net/20.500.11851/6480
ISSN: 1542-3980
1542-3999
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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