Results 151 to 160 of about 867,994 (193)

Agglomerative Fuzzy Clustering

2016
The term fuzzy clustering usually refers to prototype-based methods that optimize an objective function in order to find a (fuzzy) partition of a given data set and are inspired by the classical c-means clustering algorithm. Possible transfers of other classical approaches, particularly hierarchical agglomerative clustering, received much less ...
Christian Borgelt, Rudolf Kruse
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Fast fuzzy clustering

Fuzzy Sets and Systems, 1998
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Tai Wai Cheng, Dmitry B. Goldgof, Lawrence O. Hall   +2 more
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Collaborative fuzzy clustering

Pattern Recognition Letters, 2002
Summary: We introduce a new clustering architecture in which several subsets of patterns can be processed together with an objective of finding a structure that is common to all of them. To reveal this structure, the clustering algorithms operating on the separate subsets of data collaborate by exchanging information about local partition matrices.
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Fuzzy Clustering with Viewpoints

IEEE Transactions on Fuzzy Systems, 2010
In this study, we introduce a certain knowledge-guided scheme of fuzzy clustering in which domain knowledge is represented in the form of so-called viewpoints. Viewpoints capture a way in which the user introduces his/her point of view at the data by identifying some representatives, which, being treated as externally introduced prototypes, have to be ...
LOIA, Vincenzo, Witold Pedrycz, SENATORE, Sabrina   +2 more
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Fuzzy and possibilistic clustering for fuzzy data

Computational Statistics & Data Analysis, 2012
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COPPI, Renato, D'URSO, Pierpaolo, GIORDANI, Paolo   +2 more
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A Combination Scheme for Fuzzy Clustering

International Journal of Pattern Recognition and Artificial Intelligence, 2002
In this paper we present a voting scheme for fuzzy cluster algorithms. This voting method allows us to combine several runs of cluster algorithms resulting in a common partition. This helps us to tackle the problem of choosing the appropriate clustering method for a data set where we have no a priori information about it.
Evgenia Dimitriadou, Andreas Weingessel, Kurt Hornik   +2 more
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Cluster validity for kernel fuzzy clustering

2012 IEEE International Conference on Fuzzy Systems, 2012
This paper presents cluster validity for kernel fuzzy clustering. First, we describe existing cluster validity indices that can be directly applied to partitions obtained by kernel fuzzy clustering algorithms. Second, we show how validity indices that take dissimilarity (or relational) data D as input can be applied to kernel fuzzy clustering.
Timothy C. Havens, James C. Bezdek, Marimuthu Palaniswami   +2 more
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Fuzzy rule clustering

2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236), 2002
The concept of relevance has been proposed as a measure of the relative importance of sets of rules, allowing the development of a new methodology for organising the linguistic information: SLIM (Separation of Linguistic Information Methodology). Based on this concept and on this methodology, a new fuzzy clustering of fuzzy rules algorithm (FCFRA) is ...
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A cluster validity index for fuzzy clustering

Pattern Recognition Letters, 2005
Cluster validity indexes have been used to evaluate the fitness of partitions produced by clustering algorithms. This paper presents a new validity index for fuzzy clustering called a partition coefficient and exponential separation (PCAES) index. It uses the factors from a normalized partition coefficient and an exponential separation measure for each
Kuo-Lung Wu, Miin-Shen Yang
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A cluster validity index for fuzzy clustering

Information Sciences, 2008
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Yunjie Zhang, Weina Wang 0002, Xiaona Zhang, Yi Li   +3 more
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