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...

Ful tanımlama

Detaylı Bibliyografya
Asıl Yazarlar: Chao Zhang, Yusheng Cheng, Yibin Wang, Yuting Xu
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: Universidad Internacional de La Rioja (UNIR) 2022-09-01
Seri Bilgileri:International Journal of Interactive Multimedia and Artificial Intelligence
Konular:
conditional probability
interactive causal inference
label co-occurrence
label space reshape
multi-label classification
Online Erişim:https://www.ijimai.org/journal/bibcite/reference/3159

Internet

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

Benzer Materyaller