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Updated: May 14, 2025

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优化抑郁症分类使用组合数据集和超参数调与Optuna的优化

Ștefana Duță1, Alina Elena Sultana1

  • 1Applied Electronics and Information Engineering, National University of Science and Technology POLITEHNICA Bucharest (U.N.S.T.P.B.), 060042 Bucharest, Romania.

Sensors (Basel, Switzerland)
|April 12, 2025
PubMed
概括

这项研究优化了使用Optuna的EEGNet模型,以从EEG信号中准确地分类抑郁症. 强大的模型实现了高精度,显示了便携式临床诊断的前景.

关键词:
电脑电磁波信号处理这是EEGNet的EEA网络.优化Optuna的优化方式临床诊断 临床诊断 临床诊断抑郁症的分类 抑郁症的分类超参数调整 超参数调整机器学习是机器学习.神经网络的神经网络的神经网络

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