A survey of fuzzy clustering algorithms for pattern recognition. I
- 1 January 1999
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
- Vol. 29 (6), 778-785
- https://doi.org/10.1109/3477.809032
Abstract
Clustering algorithms aim at modeling fuzzy (i.e., ambiguous) unlabeled patterns efficiently. Our goal is to propose a theoretical framework where the expressive power of clustering systems can be compared on the basis of a meaningful set of common functional features. Part I of this paper reviews the following issues related to clustering approaches found in the literature: relative (probabilistic) and absolute (possibilistic) fuzzy membership functions and their relationships to the Bayes rule, batch and on-line learning, prototype editing schemes, growing and pruning networks, modular network architectures, topologically perfect mapping, ecological nets and neuro-fuzziness. From this discussion an equivalence between the concepts of fuzzy clustering and soft competitive learning in clustering algorithms is proposed as a unifying framework in the comparison of clustering systems. Moreover, a set of functional attributes is selected for use as dictionary entries in the comparison of clustering algorithms, which is the subject of part II of this paper.Keywords
This publication has 38 references indexed in Scilit:
- Soft vector quantization and the EM algorithmNeural Networks, 1998
- Robust clustering methods: a unified viewIEEE Transactions on Fuzzy Systems, 1997
- Optimal learning in artificial neural networks: A review of theoretical resultsNeurocomputing, 1996
- Learning without local minima in radial basis function networksIEEE Transactions on Neural Networks, 1995
- Topology representing networksNeural Networks, 1994
- Fuzzy Kohonen clustering networksPattern Recognition, 1994
- Design and evolution of modular neural network architecturesNeural Networks, 1994
- Neural Networks and the Bias/Variance DilemmaNeural Computation, 1992
- Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance systemNeural Networks, 1991
- A massively parallel architecture for a self-organizing neural pattern recognition machineComputer Vision, Graphics, and Image Processing, 1987