Differential Evolution with Competing Strategies Applied to Partitional Clustering

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F12%3AA13015SF" target="_blank" >RIV/61988987:17610/12:A13015SF - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Differential Evolution with Competing Strategies Applied to Partitional Clustering

Original language description

We consider the problem of optimal partitional clustering of real data sets by optimizing three basic criteria (trace of within scatter matrix, variance ratio criterion, and Marriottt's criterion). Four variants of the algorithm based on differential evolution with competing strategies are compared on eight real-world data sets. The experimental results showed that hybrid variants with $k$-means algorithm for a local search are essentially more efficient than the others. However, the use of Marriottt'scriterion resulted in the stopping of hybrid variants at a local minimum.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

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Project

<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2012

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Lecture Notes in Computer Science 7269

ISBN

978-3-642-29352-8

ISSN

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e-ISSN

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Number of pages

9

Pages from-to

136-144

Publisher name

Springer-Verlag

Place of publication

Berlin Heidelberg

Event location

Zakopane

Event date

Apr 29, 2012

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000314209500016