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Jun, 2012
精确的软置信加权学习
Exact Soft Confidence-Weighted Learning
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Jialei Wang, Peilin Zhao, Steven C. H. Hoi
TL;DR
本文提出了一种新的软置信度加权在线学习方法,使传统置信度加权学习方法能够处理非可分离情况,并具有大边际训练、置信度加权、处理非可分离数据和自适应边际等特性,实验结果表明,与多种最新算法相比较,该方法在预测准确性方面普遍表现更好或至少相当,但计算效率更高。
Abstract
In this paper, we propose a new
soft confidence-weighted
(SCW)
online learning
scheme, which enables the conventional confidence-weighted learning method to handle non-separable cases. Unlike the previous confide
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