Developing additive spectral approach to fuzzy clustering

Authors:
Boris G. Mirkin;Susana Nascimento
Affiliations:
Department of Computer Science, Birkbeck University of London, London, UK and School of Applied Mathematics and Informatics, Higher School of Economics, Moscow, RF;Department of Computer Science and Centre for Artificial Intelligence, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
Venue:
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
Year:
2011

Citing 5
Cited 0

Fuzzy Clustering Models and Applications

Fuzzy Clustering Models and Applications
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing

Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
A tutorial on spectral clustering

Statistics and Computing
A method of relational fuzzy clustering based on producing feature vectors using FastMap

Information Sciences: an International Journal
Robust fuzzy clustering of relational data

IEEE Transactions on Fuzzy Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

An additive spectral method for fuzzy clustering is presented. The method operates on a clustering model which is an extension of the spectral decomposition of a square matrix. The computation proceeds by extracting clusters one by one, which allows us to draw several stopping rules to the procedure. We experimentally test the performance of our method and show its competitiveness.