Badanie efektywności wybranych metod grupowania danych na zbiorach danych ze świata realnego - Korzeniowski, Jerzy (Investigating the Efficiency of Selected Data Grouping Methods on Real World Data Sets, 2009)
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)
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics; 2009; Nr 47, s. 358-366