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基于数据重平衡的AUC优化Boosting算法

李秋洁 茅耀斌

李秋洁, 茅耀斌. 基于数据重平衡的AUC优化Boosting算法. 自动化学报, 2013, 39(9): 1467-1475. doi: 10.3724/SP.J.1004.2013.01467
引用本文: 李秋洁, 茅耀斌. 基于数据重平衡的AUC优化Boosting算法. 自动化学报, 2013, 39(9): 1467-1475. doi: 10.3724/SP.J.1004.2013.01467
LI Qiu-Jie, MAO Yao-Bin. AUC Optimization Boosting Based on Data Rebalance. ACTA AUTOMATICA SINICA, 2013, 39(9): 1467-1475. doi: 10.3724/SP.J.1004.2013.01467
Citation: LI Qiu-Jie, MAO Yao-Bin. AUC Optimization Boosting Based on Data Rebalance. ACTA AUTOMATICA SINICA, 2013, 39(9): 1467-1475. doi: 10.3724/SP.J.1004.2013.01467

基于数据重平衡的AUC优化Boosting算法

doi: 10.3724/SP.J.1004.2013.01467
基金项目: 

国家科技重大专项基金(2011ZX04002-051); 国家自然科学基金(60974129, 70931002); 中央高校基本科研业务费专项资金(NUST2011Y BXM119)资助

详细信息
    作者简介:

    李秋洁 南京林业大学机械电子工程学院讲师.主要研究方向为计算机视觉,模式识别和机器学习.E-mail: liqiujie_1@163.com

AUC Optimization Boosting Based on Data Rebalance

Funds: 

Supported by the Key Research Funds of Ministry of Science and Technology (2011ZX04002-051), National Natural Science Foundation of China (60974129, 70931002), and the Fundamental Research Funds for the Central Universities (NUST2011YBX M119)

  • 摘要: 接收者操作特性(Receiver operating characteristics, ROC)曲线下面积(Area under the ROC curve, AUC)常被用于度量分类器在整个类先验分布上的总体分类性能. 原始Boosting算法优化分类精度,但在AUC度量下并非最优. 提出了一种AUC优化Boosting改进算法,通过在原始Boosting迭代中引入数据重平衡操作,实现弱学习算法优化目标从精度向AUC的迁移. 实验结果表明,较之原始Boosting算法,新算法在AUC度量下能获得更好性能.
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出版历程
  • 收稿日期:  2012-03-06
  • 修回日期:  2012-07-25
  • 刊出日期:  2013-09-20

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