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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Bibliografiska uppgifter
Huvudupphovsmän: Chao Zhang, Yusheng Cheng, Yibin Wang, Yuting Xu
Materialtyp: Artikel
Språk:English
Publicerad: Universidad Internacional de La Rioja (UNIR) 2022-09-01
Serie:International Journal of Interactive Multimedia and Artificial Intelligence
Ämnen:
conditional probability
interactive causal inference
label co-occurrence
label space reshape
multi-label classification
Länkar:https://www.ijimai.org/journal/bibcite/reference/3159

Internet

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

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