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在低密度生物数据集中优化支向量机器分析

Pablo Rivas1, Sharon Moore2, Urszula T Iwaniec3

  • 1School of Computer Science and Mathematics, Marist College, Poughkeepsie, NY, USA.

Proceedings. International Conference on Computational Science and Computational Intelligence
|August 20, 2025
PubMed
概括

机器学习,包括支持矢量机 (SVM),有效地分析来自非人类灵长类动物模型的稀疏数据,以寻找酒精使用障碍 (AUD). 相关性和SVR等特征排名策略在低样本的生物数据集中被证明是最好的.

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