Wybór wartości parametrów przez walidację wyników klasyfikacji taksonomicznej metody wektorów nośnych - Trzęsiok, Michał (On Parameter Selection and Validation of Support Vector Clustering, 2008)
Support Vector Clustering (SVC) is a new method for unsupervised classification. The advantage of this method is that no prior assumptions about the number or the shape of clusters are required. The choice of two parameters: the soft margin constant and the Gaussian kernel parameter, is crucial to the clustering solutions. In the paper the validation of SVC based on resampling techniques is proposed as a method for a parameter selection. The method was illustrated on benchmark data set from R package cluster Sim.
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics; 2008; Nr 7, s. 354-363