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Updated: Jan 16, 2026

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通过合成数据生成,提高机器学习模型在疾病预测中的性能

M Kannan1, D Umamaheswari2, B Manimekala2

  • 1Department of Computer Science, CHRIST University, Bengaluru, Karnataka, India. kannanmuthushankar@gmail.com.

Scientific reports
|September 29, 2025
PubMed
概括

本研究介绍了先进的合成数据生成技术,包括SMOTE,ADASYN和Deep-CTGAN,以解决机器学习中的不平衡数据集. 拟议的框架显著提高了关键健康数据集的分类准确性和模型稳定性.

关键词:
数据增强数据增强在深度CTGAN中.功能重要性 功能重要性在SHAP分析中,我们分析了SHAP.合成数据生成的合成数据生成.

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