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Updated: May 16, 2025

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评估基于树的集体机器学习技术对临床风险预测的样本大小要求

Oya Kalaycıoğlu1,2, Menelaos Pavlou2, Serhat E Akhanlı3

  • 1Department of Biostatistics and Medical Informatics, Bolu Abant İzzet Baysal University, Bolu, Türkiye.

Statistical methods in medical research
|May 14, 2025
PubMed
概括

使用机器学习技术 (MLT) 的临床风险模型的样本大小准则尚不清楚. 这项研究发现,针对平均绝对预测误差 (MAPE) 的现有指南对于基于树的MLT是不够的,但适合对C统计的外部验证.

关键词:
机器学习 机器学习包装包装包装包装包装包装包装包装包装包装包装提升刺激的提升.预测模型 预测模型随机的森林随机的森林样本的大小 样本大小

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