@misc{Migdał-Najman_Kamila_Analityczne_2006,
 author={Migdał-Najman, Kamila and Najman, Krzysztof},
 year={2006},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 description={Prace Naukowe Akademii Ekonomicznej we Wrocławiu. Taksonomia (13); 2006; nr 1126, s. 159-167},
 publisher={Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu},
 language={pol},
 abstract={Several clustering techniques have been proposed for the analysis of fuzzy data sets. Cluster validity indices represent useful tools to support such a task. In this paper three validation indices were applied to fourteen data sets. The resultant optimal clusters have been found to be stable for the different validity indices used, viz. Bezdek’s Partition Coefficient (PC), Classification Entropy (CE) and Separation Index (S). 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. Two indices (PC and CE) were called into question their usefulness. Index S was characterized by relatively not large errors and significant effectiveness.},
 type={artykuł},
 title={Analityczne metody ustalania liczby skupień w rozmytych zbiorach danych},
}