@misc{Korzeniowski_Jerzy_Badanie_2009,
 author={Korzeniowski, Jerzy},
 year={2009},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics; 2009; Nr 47, s. 358-366},
 language={pol},
 abstract={In their paper [Guha et al. 1998], the authors of CURE developed an algorithm that beats all so far known data grouping algorithms with respect to speed, sensitivity to outliers and capacity to find non-normal clusters. The algorithm was compared with CLARA, CLARANS and BIRCH. The comparison was carried out on a couple of artificial data sets from two-dimensional Euclidean space. In a similar way Karypis et al. [Karypis et al. 2000] proposed CHAMELEON and checked its performance on sets from two-dimensional Euclidean space. It seems worthy to investigate the performance of these two new methods on real world data sets. This is the aim of this paper. (original abstract)},
 title={Badanie efektywności wybranych metod grupowania danych na zbiorach danych ze świata realnego},
 type={artykuł},
}