Interactive Causal Correlation Space Reshape for Multi-Label Classification

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...

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Dades bibliogràfiques
Autors principals: Chao Zhang, Yusheng Cheng, Yibin Wang, Yuting Xu
Format: Article
Idioma:English
Publicat: Universidad Internacional de La Rioja (UNIR) 2022-09-01
Col·lecció:International Journal of Interactive Multimedia and Artificial Intelligence
Matèries:
conditional probability
interactive causal inference
label co-occurrence
label space reshape
multi-label classification
Accés en línia:https://www.ijimai.org/journal/bibcite/reference/3159

Internet

https://www.ijimai.org/journal/bibcite/reference/3159

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