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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Detalhes bibliográficos
Principais autores:	Chao Zhang, Yusheng Cheng, Yibin Wang, Yuting Xu
Formato:	Artigo
Idioma:	English
Publicado em:	Universidad Internacional de La Rioja (UNIR) 2022-09-01
coleção:	International Journal of Interactive Multimedia and Artificial Intelligence
Assuntos:	conditional probability interactive causal inference label co-occurrence label space reshape multi-label classification
Acesso em linha:	https://www.ijimai.org/journal/bibcite/reference/3159

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