Shedding light on the asymmetric learning capability of AdaBoost

Authors:
Iago Landesa-VáZquez;José Luis Alba-Castro
Affiliations:
Signal Theory and Communications Department, University of Vigo, Maxwell Street, 36310 Vigo, Spain;Signal Theory and Communications Department, University of Vigo, Maxwell Street, 36310 Vigo, Spain
Venue:
Pattern Recognition Letters
Year:
2012

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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.