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 [BibTeX] [Marc21]
Online Policy Adaptation for Ensemble Classifiers
Type of publication: Idiap-RR
Citation: DimitrakBengio2003b
Number: Idiap-RR-69-2003
Year: 2003
Institution: IDIAP
Note: Accepted for publication in ESANN 2004
Abstract: Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper, the idea of using an adaptive policy for training and combining the base classifiers is put forward. The effectiveness of this approach for online learning is demonstrated by experimental results on several UCI benchmark databases.
Userfields: ipdmembership={learning},
Projects Idiap
Authors Dimitrakakis, Christos
Bengio, Samy
Crossref by ESANN:DimitrakBengio2004b
Added by: [UNK]
Total mark: 0
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