Invariant hierarchical clustering schemes

Ildar Batyrshin, Tamas Rudas

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

5 Scopus citations

Abstract

A general parametric scheme of hierarchical clustering procedures with invariance under monotone of similarity values and invariance under numeration of objects is described. This scheme consists of two steps: of given similarity values between objects and transitive closure of obtained valued relation. Some theoretical properties of considered scheme are studied. Different parametric classes of clustering procedures from this scheme based on perception like "keep similarity classes," "break bridges between clusters," etc. are considered. Several examples are used to illustrate the application of proposed clustering procedures to analysis of similarity structures of data.

Original languageEnglish
Title of host publicationPerception-based Data Mining and Decision Making in Economics and Finance
EditorsIldar Batyrshin, Leonid Sheremetov, Janusz Kacprzyk, Lotfi Zadeh, Ildar Batyrshin, Leonid Sheremetov
Pages181-206
Number of pages26
DOIs
StatePublished - 2007
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume36
ISSN (Print)1860-949X

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