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- W2347695989 abstract "Boosting is an effective classifier combination method,which can improve classification performance of an unstable learning algorithm.But it dose not make much more improvement on a stable learning algorithm.BAN,i.e.BN augmented Naive-Bayes,is an augmented Bayesian network classifier,whose accuracy is easy to improve by the Boosting technique.In this paper,a wrapping classifier which wraps around GBN and BAN is compared with the Boosting-BAN classifier which is Boosting based on BAN combination classifier.Finally,experimental results show that the Boosting-BAN has higher classification accuracy on most data sets." @default.
- W2347695989 created "2016-06-24" @default.
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- W2347695989 date "2009-01-01" @default.
- W2347695989 modified "2023-09-26" @default.
- W2347695989 title "The Boosting-based BAN Combination Classifier" @default.
- W2347695989 hasPublicationYear "2009" @default.
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