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Dynamic Score Combination: A Supervised and Unsupervised Score Combination Method

机译:动态分数组合:有监督和无监督分数组合方法

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摘要

In two-class score-based problems the combination of scores from an ensemble of experts is generally used to obtain distributions for positive and negative patterns that exhibit a larger degree of separation than those of the scores to be combined. Typically, combination is carried out by a "static" linear combination of scores, where the weights are computed by maximising a performance function. These weights are equal for all the patterns, as they are assigned to each of the expert to be combined. In this paper we propose a "dynamic" formulation where the weights are computed individually for each pattern. Reported results on a biometric dataset show the effectiveness of the proposed combination methodology with respect to "static" linear combinations and trained combination rules.
机译:在基于两类分数的问题中,通常使用来自专家组的分数组合来获得正向和负向模式的分布,这些正向和负向模式表现出比要组合的分数更大的分离度。通常,通过分数的“静态”线性组合来执行组合,其中权重是通过最大化性能函数来计算的。这些权重对于所有模式都是相等的,因为它们被分配给每个要组合的专家。在本文中,我们提出了一种“动态”公式,其中权重针对每种模式分别计算。生物统计数据集上的报告结果表明,相对于“静态”线性组合和经过训练的组合规则,所提出的组合方法是有效的。

著录项

  • 来源
  • 会议地点 Leipzig(DE);Leipzig(DE)
  • 作者单位

    DIEE Department of Electrical and Electronic Engineering, University of Cagliari,09123 Cagliari, Italy;

    rnDIEE Department of Electrical and Electronic Engineering, University of Cagliari,09123 Cagliari, Italy;

    rnDIEE Department of Electrical and Electronic Engineering, University of Cagliari,09123 Cagliari, Italy;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机的应用;
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