ALTERNATIVE TERMINATION CRITERION FOR K-SPECIFIED CRISP DATA CLUSTERING ALGORITHMS

Volodymyr  Mosorov; Taras  Panskyi; Sebastian  Biedron

doi:10.5604/01.3001.0010.5216

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Published: Sep 30, 2017

DOI: https://doi.org/10.5604/01.3001.0010.5216

Issue Vol. 7 No. 3 (2017)

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ALTERNATIVE TERMINATION CRITERION FOR K-SPECIFIED CRISP DATA CLUSTERING ALGORITHMS
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DOI

https://doi.org/10.5604/01.3001.0010.5216

Authors

Volodymyr Mosorov

w.mosorow@kis.p.lodz.pl

Lodz University of Technology, Institute of Applied Computer Science, Poland

Taras Panskyi

tpanski@kis.p.lodz.pl

Lodz University of Technology, Institute of Applied Computer Science, Poland

Sebastian Biedron

sbiedron@iis.p.lodz.pl

Lodz University of Technology, Institute of Applied Computer Science, Poland

Abstract

In this paper the analysis of k-specified (namely k-means) crisp data partitioning pre-clustering algorithm’s termination criterion performance is described. The results have been analyzed using the clustering validity indices. Termination criterion allows analyzing data with any number of clusters. Moreover, introduced criterion in contrast to the known validity indices enables to analyze data that make up one cluster.

Keywords:

pre-clustering algorithm, internal validity measures

References

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Mosorov, V. ., Panskyi, T. ., & Biedron, S. . (2017). ALTERNATIVE TERMINATION CRITERION FOR K-SPECIFIED CRISP DATA CLUSTERING ALGORITHMS. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 7(3), 56–59. https://doi.org/10.5604/01.3001.0010.5216

ALTERNATIVE TERMINATION CRITERION FOR K-SPECIFIED CRISP DATA CLUSTERING ALGORITHMS

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