Shedding Light on the Asymmetric Learning Capability of AdaBoost
Machine Learning
2015-07-15 v1 Artificial Intelligence
Computer Vision and Pattern Recognition
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.
Cite
@article{arxiv.1507.02084,
title = {Shedding Light on the Asymmetric Learning Capability of AdaBoost},
author = {Iago Landesa-Vázquez and José Luis Alba-Castro},
journal= {arXiv preprint arXiv:1507.02084},
year = {2015}
}