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Optimizing area under the ROC curve via extreme learning machines

机译：通过极限学习机优化ROC曲线下的面积

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摘要

Recently, Extreme learning machine (ELM), an efficient training algorithm for single-hidden-layer feed forward neural networks (SLFN), has gained increasing popularity in machine learning communities. In this paper the ELM based Area Under the ROC Curve (AUC) optimization algorithms are studied so as to further improve the performance of ELM for imbalanced datasets. For binary class problems, a novel ELM algorithm is proposed based on an efficient least square method. For multi-class problems, the following works are done in this paper: First of all, theoretical comparison analysis is proposed for the potential multi-class extensions of AUC; Secondly, a unified objective function for multi-class AUC optimization is proposed following the theoretical analysis; Subsequently, two ELM based multi-class AUC optimization algorithms called ELMMAUC and ELmacroAUC respectively are proposed followed with complexity analyses; Finally, the generalization analysis is established for ELMMAUC in search of theoretical supports. Empirical study on a variety of real-world datasets show the effectiveness of our proposed algorithms. (C) 2017 Elsevier B.V. All rights reserved.
机译：最近，极限学习机（ELM）是一种用于单隐藏前馈神经网络（SLFN）的有效训练算法，在机器学习社区中越来越受欢迎。本文研究了基于ELM的ROC曲线下面积（AUC）优化算法，以进一步提高不平衡数据集的ELM性能。针对二元类问题，提出了一种基于有效最小二乘法的新型ELM算法。对于多类问题，本文做了以下工作：首先，对AUC的潜在多类扩展提出了理论比较分析。其次，在理论分析的基础上，提出了用于多类AUC优化的统一目标函数。随后，分别提出了两种基于ELM的多类AUC优化算法ELMMAUC和ELmacroAUC，并进行了复杂度分析。最后，为ELMMAUC建立了归纳分析，以寻求理论上的支持。对各种现实世界数据集的经验研究表明，我们提出的算法是有效的。 （C）2017 Elsevier B.V.保留所有权利。

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  • 来源
    《Knowledge-Based Systems》 |2017年第15期|74-89|共16页
  • 作者

    Yang Zhiyong; Zhang Taohong; Lu Jingcheng; Zhang Dezheng; Kalui Dorothy;

  • 作者单位

    Univ Sci & Technol Beijing, Dept Comp, Sch Comp & Commun Engn, Beijing 100083, Peoples R China|Beijing Key Lab Knowledge Engn Mat Sci, Beijing 100083, Peoples R China;

    Univ Sci & Technol Beijing, Dept Comp, Sch Comp & Commun Engn, Beijing 100083, Peoples R China|Beijing Key Lab Knowledge Engn Mat Sci, Beijing 100083, Peoples R China;

    Univ Sci & Technol Beijing, Dept Comp, Sch Comp & Commun Engn, Beijing 100083, Peoples R China;

    Univ Sci & Technol Beijing, Dept Comp, Sch Comp & Commun Engn, Beijing 100083, Peoples R China|Beijing Key Lab Knowledge Engn Mat Sci, Beijing 100083, Peoples R China;

    Univ Sci & Technol Beijing, Dept Comp, Sch Comp & Commun Engn, Beijing 100083, Peoples R China|Beijing Key Lab Knowledge Engn Mat Sci, Beijing 100083, Peoples R China;

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  • 正文语种 eng
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  • 关键词

    Extreme learning machine (ELM); Area under the ROC curve (AUC); Imbalanced datasets; Multi-class AUC optimization;

    机译：极限学习机（ELM）;ROC曲线下的面积（AUC）;数据集不平衡;多类AUC优化;

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