@misc{Trzęsiok_Michał_Propozycja_2009,
 author={Trzęsiok, Michał and Trzęsiok, Joanna},
 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 86, s. 65-74},
 language={pol},
 abstract={After building the classification model, at the stage of the class description we try to extract knowledge from the model. We search for the description of classification rules, the natural language. The paper presents the simple algorithm for building the ranking of predictor variables based on their descriptive power (for every class separately) and uses boxplots to enable interpretation and give some insight. The procedure is universal and can be applied to classic or data mining methods. SVMs, Random Forest, Neural Network and k-Nearest Neighbours were used for illustration with R software.},
 title={Propozycja metody wizualizacji wyników klasyfikacji wspomagającej profilowanie klas},
 type={artykuł},
}