Randomized multi-label subproblems concatenation via error correcting output codes-Reference-Cited by-同舟云学术

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Randomized multi-label subproblems concatenation via error correcting output codes

Published:2020-10 Issue: Volume:410 Page:317-327
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Shan Jincheng,Hou Chenping,Tao Hong,Zhuge Wenzhang,Yi Dongyun

Funder

NSF

Distinguished Young Scholars of Hunan Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference47 articles.

1. Parametric mixture models for multi-labeled text;Ueda,2002

2. A review on automatic image annotation techniques;Zhang;Pattern Recogn.,2012

3. Correlative multi-label video annotation;Qi,2007

4. Polyphonic music information retrieval based on multi-label cascade classification system;Jiang;Proquest Llc,2009

5. A review on multi-label learning Algorithms;Zhang;IEEE Trans. Knowl. Data Eng.,2014

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2. Multi-label Text Categorization using Error-correcting Output Coding with Weighted Probability;International Journal of Engineering;2022

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