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Updated: Jun 9, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
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Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

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注意:用于可解释的信用评分的非参数过量抽样技术

Seongil Han1, Haemin Jung2, Paul D Yoo3

  • 1School of Computing & Mathematical Sciences, University of London, Birkbeck College, London, UK.

Scientific reports
|October 31, 2024
PubMed
概括

一种新方法,即可解释信用评分的非参数过量采样技术 (NOTE),可以在不平衡的数据集上提高信用评分的准确性. 它提高了模型的稳定性和可解释性,优于金融风险评估的现有过量抽样技术.

关键词:
有条件的瓦斯斯坦生成对抗网络.信用评分是指信用评分.可解释的人工智能不平衡的阶级是不平衡的.过量采样过度采样堆叠的自动编码器

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