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Updated: Feb 25, 2026

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
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Published on: August 18, 2023

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监督学习用于预测柔性拉索中的未知修改变量.

Zainab Subhi Mahmood Hawrami1, Mehmet Ali Cengiz2, Emre Dünder3

  • 1Ministry of Higher Education and Scientific Research-KRG, Erbil, Iraq.

Scientific reports
|February 23, 2026
PubMed
概括

估计隐藏变量对于使用柔性拉索模型进行准确预测至关重要. 基于树的模型在修饰者估计方面表现出色,而规范化的模型可以改善最终结果的预测.

关键词:
机器学习是机器学习.修改变量的变量柔软的拉索模型模型预测变量是一个预测变量.监督学习算法监督学习算法

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