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Erschienen in:
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2012 | OriginalPaper | Buchkapitel

4. Incremental Spectral Clustering

verfasst von : Abdelhamid Bouchachia, Markus Prossegger

Erschienen in: Learning in Non-Stationary Environments

Verlag: Springer New York

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Abstract

In the present contribution, a novel algorithm for off-line spectral clustering algorithm is introduced and an online extension is derived in order to deal with sequential data. The proposed algorithm aims at dealing with nonconvex clusters having different forms. It relies on the notion of communicability that allows to handle the contiguity of data distribution. In the second part of the paper, an incremental extension of the fuzzy c-varieties is proposed to serve as a building block of the incremental spectral clustering algorithm (ISC). Initial simulations are presented towards the end of the contribution to show the performance of the ISC algorithm.

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Vorheriges Kapitel A Granular Description of Data: A Study in Evolvable Systems
Nächstes Kapitel Semisupervised Dynamic Fuzzy K-Nearest Neighbors
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Metadaten
Titel
Incremental Spectral Clustering
verfasst von
Abdelhamid Bouchachia
Markus Prossegger
Copyright-Jahr
2012
Verlag
Springer New York
Buch
Learning in Non-Stationary Environments

Print ISBN: 978-1-4419-8019-9

Electronic ISBN: 978-1-4419-8020-5

Copyright-Jahr: 2012

DOI
https://doi.org/10.1007/978-1-4419-8020-5_4

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