ALTERNATIVE TERMINATION CRITERION FOR K-SPECIFIED CRISP DATA CLUSTERING ALGORITHMS

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DOI

Volodymyr Mosorov

w.mosorow@kis.p.lodz.pl

Taras Panskyi

tpanski@kis.p.lodz.pl

Sebastian Biedron

sbiedron@iis.p.lodz.pl

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

Article Details

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