@misc{Migdał-Najman_Kamila_Analityczne_2005,
 author={Migdał-Najman, Kamila and Najman, Krzysztof},
 year={2005},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 description={Prace Naukowe Akademii Ekonomicznej we Wrocławiu. Taksonomia (12); 2005; nr 1076, s. 265-273},
 publisher={Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu},
 language={pol},
 abstract={Several clustering techniques have been proposed for the analysis of data sets. Cluster validity indices represent useful tools to support such a task. They are particularly relevant in applications in which there is not a priori indication of the actual number of clusters. In this paper two validation indices were applied to fifteen data sets, using different intracluster and intercluster distances. The resultant optimal clusters have been found to be stable for the different validity indices used, viz. Davies-Bouldin Index and Dunn's Index. It was shown that these methods might support the prediction of the optimal cluster partitioning for those data sets but the determination of the optimal number of clusters is an open problem.},
 type={artykuł},
 title={Analityczne metody ustalania liczby skupień},
}