The Modification of the K-means Method for Creating Non-convex Clusters

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The Modification of the K-means Method for Creating Non-convex Clusters

Popis výsledku v původním jazyce

Cluster analysis involves many different methods based on a variety of principles. Each of these methods has its advantages and disadvantages. The aim of authors of the new algorithms is to search for new methods that use existing methods positives and minimize the negatives. In this article, we discuss one of the most famous and most used method, the k-means method. The inability to search non-convex clusters is one of known weak points of the k-means method. Nevertheless, this method has many advantages such as simplicity and speed. This algorithm is also implemented in a lot of statistical software. The article presents a proposal for a solution. The second phase of the process is proposed. We create a certain number of clusters which is larger thandesired in the first stage of processing by the classical algorithm k-means. Then we combine some clusters using appropriate agglomerative methods and reduce the number of clusters required in the second phase. There is the proposed proc

Název v anglickém jazyce

The Modification of the K-means Method for Creating Non-convex Clusters

Popis výsledku anglicky

Cluster analysis involves many different methods based on a variety of principles. Each of these methods has its advantages and disadvantages. The aim of authors of the new algorithms is to search for new methods that use existing methods positives and minimize the negatives. In this article, we discuss one of the most famous and most used method, the k-means method. The inability to search non-convex clusters is one of known weak points of the k-means method. Nevertheless, this method has many advantages such as simplicity and speed. This algorithm is also implemented in a lot of statistical software. The article presents a proposal for a solution. The second phase of the process is proposed. We create a certain number of clusters which is larger thandesired in the first stage of processing by the classical algorithm k-means. Then we combine some clusters using appropriate agglomerative methods and reduce the number of clusters required in the second phase. There is the proposed proc

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

8th International Days of Statistics and Economics

ISBN

978-80-87990-02-5

ISSN

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e-ISSN

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Počet stran výsledku

9

Strana od-do

1722-1730

Název nakladatele

Melandrium

Místo vydání

Slaný

Místo konání akce

Praha

Datum konání akce

11. 9. 2014

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

000350226700169