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Updated: Sep 16, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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在有噪音标签的学习中,用于样本选择的异常修剪的双间隔光滑损失

Senyu Hou1, Maolong Xu1, Gaoxia Jiang1

  • 1School of Computer and Information Technology, Shanxi University, Taiyuan, Shanxi, 030006, China.

Neural networks : the official journal of the International Neural Network Society
|July 11, 2025
PubMed
概括

这项研究引入了异常修剪双间隔平滑 (OTDIS) 损失,以提高深度神经网络 (DNN) 在带有噪音标签的数据集上的性能. OTDIS提高了样本选择的准确性,减少了过拟合,提高了分类性能.

关键词:
深度神经网络是一种深度神经网络.学习与杂的标签学习.损失平滑,可以平滑损失.异常值经过修剪后可以得到.样本的选择 样本的选择

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