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2000
Volume 8, Issue 2
  • ISSN: 1573-4110
  • E-ISSN: 1875-6727

Abstract

Bagging and boosting have become increasingly important ensemble methods for combining models in the data mining and machine learning literature. We review the basic ideas of these methods, propose a new robust boosting algorithm based on a non-convex loss function and compare the performance of these methods to both simulated and real data sets with and without contamination.

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/content/journals/cac/10.2174/157341112800392599
2012-04-01
2025-01-14
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