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Agglomerative Fuzzy Clustering
2016The 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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Fuzzy Clustering of Ecological Data
1991Ordination and classification have always been important stages in ecological data analysis. This paper presents a clustering technique based on fuzzy sets to obtain both ordination and classification particularly well suited for ecological analyses.
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Collaborative fuzzy clustering
Pattern Recognition Letters, 2002Summary: 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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Proceedings of 1995 IEEE International Conference on Evolutionary Computation, 2002
Genetic algorithms and evolutionary programming methods are employed to perform fuzzy clustering. The experimental results are compared favourably against that of the fuzzy c-means algorithm, and their theoretical justification is given.
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Genetic algorithms and evolutionary programming methods are employed to perform fuzzy clustering. The experimental results are compared favourably against that of the fuzzy c-means algorithm, and their theoretical justification is given.
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