Results 301 to 310 of about 172,977 (352)

Evolving fuzzy clusters

IEEE International Conference on Neural Networks, 2002
An alternate training technique for the fuzzy min-max clustering neural network is introduced. The original fuzzy min-max clustering neural network utilized an algorithm similar to leader clustering and adaptive resonance theory to place hyperboxes in the pattern space.
David B. Fogel, Patrick K. Simpson
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Fuzziness indices for fuzzy clustering

The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03., 2004
Some indices of fuzziness are introduced for providing helpful information in fuzzy clustering. These indices play an auxiliary role in fuzzy clustering and can be used for deciding the number of clusters by combining with another criterion. Numerical examples are given for demonstrating how these indices can be applied.
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Clustering by a fuzzy metric

Fuzzy Sets and Systems, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hideki Kamimura, Masami Kurano
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Fuzzy clustering with supervision

Pattern Recognition, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Witold Pedrycz, George Vukovich
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Fuzzy Clustering and Fuzzy Co-clustering

2019
Fuzzy co-clustering is a fundamental technique for summarizing the structural characteristics of cooccurrence information. In this chapter, following the brief introduction of fuzzy c-Means (FCM) clustering, FCM-induced fuzzy co-clustering model is reviewed with illustrative examples.
Tin-Chih Toly Chen, Katsuhiro Honda
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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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Dynamic fuzzy clustering using fuzzy cluster loading

International Journal of General Systems, 2006
When we obtain clusters through the classification of a given data it is important to interpret the meaning of the obtained clusters. This is particularly true in the clustering of 3-way asymmetric similarity data. This is true because the asymmetric property and the structure of similarity in each cluster are changed over the time periods (or ...
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On Hesitant Fuzzy Clustering and Clustering of Hesitant Fuzzy Data

2017
Since the notion of hesitant fuzzy set was introduced, some clustering algorithms have been proposed to cluster hesitant fuzzy data. Beside of hesitation in data, there is some hesitation in the clustering (classification) of a crisp data set. This hesitation may be arise in the selection process of a suitable clustering (classification) algorithm and ...
Laya Aliahmadipour, Vicenç Torra, Esfandiar Eslami   +2 more
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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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Bayesian Fuzzy Clustering

IEEE Transactions on Fuzzy Systems, 2015
We present a Bayesian probabilistic model and inference algorithm for fuzzy clustering that provides expanded capabilities over the traditional Fuzzy C-Means approach. Additionally, we extend the Bayesian Fuzzy Clustering model to handle a variable number of clusters and present a particle filter inference technique to estimate the model parameters ...
Taylor C. Glenn, Alina Zare, Paul D. Gader   +2 more
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