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基于差异性的分类器集成:有效性分析及优化集成

杨春 殷绪成 郝红卫 闫琰 王志彬<

杨春, 殷绪成, 郝红卫, 闫琰, 王志彬40(4): 660-674. doi: 10.3724/SP.J.1004.2014.00660
引用本文: 杨春, 殷绪成, 郝红卫, 闫琰, 王志彬<. 基于差异性的分类器集成:有效性分析及优化集成. 自动化学报, 2014, 40(4): 660-674. doi: 10.3724/SP.J.1004.2014.00660
YANG Chun, YIN Xu-Cheng, HAO Hong-Wei, YAN Yan, WANG Zhi-BinACTA AUTOMATICA SINICA, 2014, 40(4): 660-674. doi: 10.3724/SP.J.1004.2014.00660
Citation: YANG Chun, YIN Xu-Cheng, HAO Hong-Wei, YAN Yan, WANG Zhi-Bin<. Classifier Ensemble with Diversity:Effectiveness Analysis and Ensemble Optimization. ACTA AUTOMATICA SINICA, 2014, 40(4): 660-674. doi: 10.3724/SP.J.1004.2014.00660

基于差异性的分类器集成:有效性分析及优化集成

doi: 10.3724/SP.J.1004.2014.00660
基金项目: 

国家自然科学基金(61105018,61175020)资助

详细信息
    作者简介:

    杨春 北京科技大学博士研究生.主要研究方向为图像处理与模式识别.E-mail:ych.learning@gmail.com

Classifier Ensemble with Diversity:Effectiveness Analysis and Ensemble Optimization

Funds: 

Supported by National Natural Science Foundation of China (61105018, 61175020)

  • 摘要: 差异性是分类器集成具有高泛化能力的必要条件. 然而,目前对差异性度量、有效性及分类器优化集成都没有统一的分析和处理方法. 针对上述问题,本文一方面从差异性度量方法、差异性度量有效性分析和相应的分类器优化集成技术三个角度,全面总结与分析了基于差异性的分类器集成. 同时,本文还通过向量空间模型形象地论证了差异性度量的有效性. 另一方面,本文针对多种典型的基于差异性的分类器集成技术(Bagging,boosting GA-based,quadratic programming (QP)、semi-definite programming (SDP)、regularized selective ensemble (RSE))在UCI数据库和USPS数据库上进行了对比实验与性能分析,并对如何选择差异性度量方法和具体的优化集成技术给出了可行性建议.
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  • 收稿日期:  2012-09-24
  • 修回日期:  2013-01-11
  • 刊出日期:  2014-04-20

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