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2005 | nr 1064 Pozyskiwanie wiedzy i zarządzanie wiedzą | 268--279
Tytuł artykułu

Pozyskiwanie wiedzy z danych przy wykorzystaniu klasyfikatorów złożonych

Autorzy
Warianty tytułu
Knowledge Acquisition from Data Using Ensemble Classifiers
Języki publikacji
PL
Abstrakty
Omówiono podstawy i metody budowy klasyfikatorów złożonych, które to klasyfikatory stanowią obecnie jeden z bardziej dynamicznie rozwijający się kierunek dziedziny pozyskiwania wiedzy z danych. Zaprezentowano wyniki badania, którego celem było sprawdzenie możliwości poprawy jakości pojedynczego drzewa decyzyjnego, wygenerowanego z algorytmem pozyskującym wiedzę systemu klasyfikatorów, poprzez wstępną redukcję komitetu przy użyciu zaproponowanej metody wyboru drzew.
EN
The article discusses main problems connected to the issues of knowledge discovery from data using heterogenous ensemble classifiers (or committee). There are presented main types of such classifiers and their architectures, methods of building and ways of making decisions. In this study are described main achievements in this domain and theoretical backgrounds, which explain principles and interesting properties of committee classifiers. The article also points to the need of knowledge extraction from ensemble of classifiers and within the framework of this domain there is presented a short survey of some used techniques and knowledge extraction methods. The study contains proposal of the method of knowledge extraction from ensemble classifiers based on reduction of number of simple classifiers , which are a part of ensemble (in particularly decision trees), and on using Trepan algorithm. To show the legitimacy of proposed method there are presented descriptions of experiments, along with analyses of their results. As a completion there are presented proposals of some improvements, which demand yet further analysis and research.(original abstract)
Twórcy
Bibliografia
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Typ dokumentu
Bibliografia
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