Robust Multi-Label Classification with Enhanced Global and Local Label Correlation

Data representation is of significant importance in minimizing multi-label ambiguity. While most researchers intensively investigate label correlation, the research on enhancing model robustness is preliminary. Low-quality data is one of the main reasons that model robustness degrades. Aiming at the...

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Egile Nagusiak:	Tianna Zhao, Yuanjian Zhang, Witold Pedrycz
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2022-05-01
Saila:	Mathematics
Gaiak:	multi-label classification label correlations noisy features missing labels robustness
Sarrera elektronikoa:	https://www.mdpi.com/2227-7390/10/11/1871
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