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...

Полное описание

Библиографические подробности
Главные авторы:	Chao Zhang, Yusheng Cheng, Yibin Wang, Yuting Xu
Формат:	Статья
Язык:	English
Опубликовано:	Universidad Internacional de La Rioja (UNIR) 2022-09-01
Серии:	International Journal of Interactive Multimedia and Artificial Intelligence
Предметы:	conditional probability interactive causal inference label co-occurrence label space reshape multi-label classification
Online-ссылка:	https://www.ijimai.org/journal/bibcite/reference/3159

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