Improved Double-Layer Structure Multilabel Classification Model via Optimal Sequence and Attention Mechanism
Multilabel classification is a key research topic in the machine learning field. In this study, the author put forward a two/two-layer chain classification algorithm with optimal sequence based on the attention mechanism. This algorithm is a classification model with a two-layer structure. By introd...
Saved in:
Main Authors: | Geqiao Liu, Mingjie Tan |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2022/7413588 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multilabel Image Annotation Based on Double-Layer PLSA Model
by: Jing Zhang, et al.
Published: (2014-01-01) -
Leveraging Partial Labels for Cervical Lesion Classification via a Multilabel Approach
by: Margaret Dy Manalo, et al.
Published: (2025-01-01) -
Relation Classification via Recurrent Neural Network with Attention and Tensor Layers
by: Runyan Zhang, et al.
Published: (2018-09-01) -
Double Attention: An Optimization Method for the Self-Attention Mechanism Based on Human Attention
by: Zeyu Zhang, et al.
Published: (2025-01-01) -
Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention Mechanism
by: Jianrui Chen, et al.
Published: (2020-01-01)