Overview Statistic: PDF-Downloads (blue) and Frontdoor-Views (gray)
  • Treffer 13 von 22
Zurück zur Trefferliste

Clustering by using a simplex structure

Zitieren Sie bitte immer diese URN: urn:nbn:de:0297-zib-7782
  • In this paper we interpret clustering as a mapping of data into a simplex. If the data itself has simplicial struture this mapping becomes linear. Spectral analysis is an often used tool for clustering data. We will show that corresponding singular vectors or eigenvectors comprise simplicial structure. Therefore they lead to a cluster algorithm, which consists of a simple linear mapping. An example for this kind of algorithms is the Perron cluster analysis (PCCA). We have applied it in practice to identify metastable sets of molecular dynamical systems. In contrast to other algorithms, this kind of approach provides an a priori criterion to determine the number of clusters. In this paper we extend the ideas to more general problems like clustering of bipartite graphs.

Volltext Dateien herunterladen

Metadaten exportieren

Weitere Dienste

Teilen auf Twitter Suche bei Google Scholar Statistik - Anzahl der Zugriffe auf das Dokument
Metadaten
Verfasserangaben:Marcus Weber
Dokumentart:ZIB-Report
Freies Schlagwort / Tag:Perron cluster analysis; bipartite graphs; cluster algorithms; stochastic matrices
MSC-Klassifikation:62-XX STATISTICS / 62Hxx Multivariate analysis [See also 60Exx] / 62H30 Classification and discrimination; cluster analysis [See also 68T10]
65-XX NUMERICAL ANALYSIS / 65Fxx Numerical linear algebra / 65F15 Eigenvalues, eigenvectors
Datum der Erstveröffentlichung:19.12.2003
Schriftenreihe (Bandnummer):ZIB-Report (04-03)
ZIB-Reportnummer:04-03
Accept ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.