A cost-sensitive attention temporal convolutional network based on adaptive top-k differential evolution for imbalanced time-series classification

• المؤلفون الرئيسيون: Zhang, Xiaocai, Peng, Hui, Zhang, Jianjia, Wang, Yang
• مؤلفون آخرون: School of Biological Sciences
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Science::Biological sciences; Imbalanced; Time-Series Classification
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/164678

Imbalanced time-series classification (ITSC) is ubiquitous in many real-world applications. In this study, a novel cost-sensitive deep learning framework, namely ACS-ATCN, is proposed for ITSC. With the framework of ACS-ATCN, first, weighted class costs are optimized jointly with the hyperparameters...