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Shedding Light on the Asymmetric Learning Capability of AdaBoost
- Source :
- Pattern Recognition Letters 33 (2012) 247-255
- Publication Year :
- 2015
-
Abstract
- In this paper, we propose a different insight to analyze AdaBoost. This analysis reveals that, beyond some preconceptions, AdaBoost can be directly used as an asymmetric learning algorithm, preserving all its theoretical properties. A novel class-conditional description of AdaBoost, which models the actual asymmetric behavior of the algorithm, is presented.
Details
- Database :
- arXiv
- Journal :
- Pattern Recognition Letters 33 (2012) 247-255
- Publication Type :
- Report
- Accession number :
- edsarx.1507.02084
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1016/j.patrec.2011.10.022