@misc{Rozmus_Dorota_Zastosowanie_2009,
 author={Rozmus, Dorota},
 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. 189-195},
 language={pol},
 abstract={Ensemble approach has been successfully applied in the context of supervised learning to increase the accuracy and stability of classification. Recently, analogous techniques for cluster analysis have been suggested. The main aim of this article is to introduce one of the ensemble techniques in taxonomy [Dudoit, Fridlyand 2003] and to compare the accuracy of classification with traditional algorithms. The novelty of this article flows from the fact of joining proposed by Dudoid and Fridlyand [2003] bagging technique in taxonomy with the concept of describing the objects by co-occurrence (co-association) matrix [Fred, Jain 2002]. In this matrix objects are described by some distance measure showing the similarity between objects. (original abstract)},
 title={Zastosowanie macierzy współwystąpień w metodzie bagging w taksonomii},
 type={artykuł},
}