Interactive Causal Correlation Space Reshape for Multi-Label Classification
Most existing multi-label classification models focus on distance metrics and feature spare strategies to extract specific features of labels. Those models use the cosine similarity to construct the label correlation matrix to constraint solution space, and then mine the latent semantic information...
Үндсэн зохиолчид: | Chao Zhang, Yusheng Cheng, Yibin Wang, Yuting Xu |
---|---|
Формат: | Өгүүллэг |
Хэл сонгох: | English |
Хэвлэсэн: |
Universidad Internacional de La Rioja (UNIR)
2022-09-01
|
Цуврал: | International Journal of Interactive Multimedia and Artificial Intelligence |
Нөхцлүүд: | |
Онлайн хандалт: | https://www.ijimai.org/journal/bibcite/reference/3159 |
Ижил төстэй зүйлс
-
Application of Label Correlation in Multi-Label Classification: A Survey
-н: Shan Huang, зэрэг
Хэвлэсэн: (2024-10-01) -
Robust Multi-Label Classification with Enhanced Global and Local Label Correlation
-н: Tianna Zhao, зэрэг
Хэвлэсэн: (2022-05-01) -
Soft-label recover based label-specific features learning
-н: Jiansheng Jiang, зэрэг
Хэвлэсэн: (2024-10-01) -
ATC-NLSP: Prediction of the Classes of Anatomical Therapeutic Chemicals Using a Network-Based Label Space Partition Method
-н: Xiangeng Wang, зэрэг
Хэвлэсэн: (2019-09-01) -
Joint Label-Density-Margin Space and Extreme Elastic Net for Label-Specific Features
-н: Gensheng Pei, зэрэг
Хэвлэсэн: (2019-01-01)