Podejście wielomodelowe z wykorzystaniem metody boosting w analizie danych symbolicznych
Ensemble learning with the application of boosting in symbolic data analysis
Author(s): Marcin PełkaSubject(s): Economy
Published by: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Keywords: symbolic data analysis; ensemble learning; boosting
Summary/Abstract: The aim of this paper is to present the application of boosting method in ensemble learning for symbolic data with the application of k-nearest neighbour method as the base classifier. The article presents basic terms of symbolic data, k-nearest neighbour classification rule for symbolic data. In the empirical part the results of application of ensemble learning for symbolic data applied for credit data set are presented.
Journal: Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
- Issue Year: 2012
- Issue No: 242
- Page Range: 315-322
- Page Count: 8
- Language: Polish
