@misc{Migdał-Najman_Kamila_Propozycja_2007,
 author={Migdał-Najman, Kamila},
 year={2007},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 description={Prace Naukowe Akademii Ekonomicznej we Wrocławiu. Taksonomia (14); 2007; nr 1169, s. 305-313},
 language={pol},
 abstract={The present article is mainly designed to study the effect of join the hierarchical agglomerative clustering and the Self Organizing Map (SOM). First, the original data set is represented using a smaller set of prototype clusters, which allows efficient use of hierarchical agglomerative clustering to divide the prototypes into groups. The reduction of the computational cost is especially important for hierarchical algorithms allowing clusters of arbitrary size and shape. Second, the 2-D gird allows rough visual presentation, classify original data to clusters and interpretation of the clusters. The clustering results using SOM as an intermediate step was also comparable with the results obtained directly from the data.},
 type={artykuł},
 title={Propozycja hybrydowej metody grupowania dużych zbiorów danych wykorzystującej sieć Kohonena i taksonomiczne metody grupowania},
}