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基于树的SIMCA用于处理异质和稀疏的数据

Robert van Vorstenbosch1, Frederik-Jan van Schooten2, Zlatan Mujagic3

  • 1Department of Pharmacology and Toxicology, Maastricht University, the Netherlands; NUTRIM Institute of Nutrition and Translational Research in Metabolism, Maastricht University, the Netherlands; Institute of Risk Assessment Sciences, Population Health Sciences, Utrecht University, the Netherlands.

Analytica chimica acta
|December 6, 2025
PubMed
概括

基于树的方法改善了omics数据的一类分类 (OCC),解决了传统SIMCA的局限性. 无监督随机森林-SIMCA (URF-SIMCA) 为欧米克数据集提供了卓越的性能和可解释性.

关键词:
隔离森林是一个孤立的森林.非线性 非线性俄米克斯 (Omics) 是一个电子游戏.伪样本采集是一种伪样本.软独立模拟类类类比的软独立模型.在 URF-SIMCA 中.没有监督的随机森林.

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