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Updated: Jun 15, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
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加速和可解释的斜随机生存森林

Byron C Jaeger1, Sawyer Welden1, Kristin Lenoir1

  • 1Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC.

Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America
|August 26, 2024
PubMed
概括

我们开发了一种更快的斜随机生存森林 (RSF) 和一种新的变量重要性 (VI) 方法. 这种方法提高了计算效率,并准确地确定了生存分析中的重要预测因素.

关键词:
计算效率 计算效率 计算效率监督学习学习 监督学习变量的重要性变量.

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