Clustering Categorical Data Using a Swarm-based Method

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F09%3A86077774" target="_blank" >RIV/61989100:27240/09:86077774 - 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

Clustering Categorical Data Using a Swarm-based Method

Original language description

The K-Modes algorithm is one of the most popular clustering algorithms in dealing with categorical data. But the random selection of starting centers in this algorithm may lead to different clustering results and falling into local optima. In this paperwe proposed a swarm-based K-Modes algorithm. The experimental results over two well known Soybean and Congressional voting categorical data sets show that our method can find the optimal global solutions and can make up the K-Modes shortcoming.

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

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2009

Confidentiality

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

Article name in the collection

World Congress on Nature &amp; Biologically Inspired Computing, 2009. NaBIC 2009

ISBN

978-1-4244-5053-4

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

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Publisher name

IEEE Computer Society

Place of publication

Los Alamitos, California

Event location

Indie

Event date

Dec 9, 2009

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000288686500309