Developing Additive Spectral Approach to Fuzzy Clustering

Susana Maria dos Santos Nascimento M. de Almeida

doi:10.1007/978-3-642-21881-1_43

Developing Additive Spectral Approach to Fuzzy Clustering

Susana Maria dos Santos Nascimento M. de Almeida

DI - Departamento de Informática

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	Unknown
Title of host publication	Lecture Notes in Computer Science (LNCS)
Pages	273-277
DOIs	https://doi.org/10.1007/978-3-642-21881-1_43
Publication status	Published - 1 Jan 2011
Event	International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2011) - Duration: 1 Jan 2011 → …

Conference

Conference	International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2011)
Period	1/01/11 → …

Access to Document

10.1007/978-3-642-21881-1_43

Cite this

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title = "Developing Additive Spectral Approach to Fuzzy Clustering",

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.",

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AB - 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.

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DO - 10.1007/978-3-642-21881-1_43

M3 - Conference contribution

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BT - Lecture Notes in Computer Science (LNCS)

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