Keyword

label correlation

Description: A statistical relationship among target labels in multi-label learning, used to represent how the presence or values of labels co-vary.

Primary topic: Text and Document Classification Technologies (55%)

OpenAlex ID: keywords/label-correlation

Classifier chains for multi-label classification

2011 · Jesse Read, Bernhard Pfahringer, et al. · Machine Learning · 2,293

PDF

Random k-Labelsets: An Ensemble Method for Multilabel Classification

2007 · Grigorios Tsoumakas, Ioannis Vlahavas · Lecture notes in computer science · 919

Classifier Chains for Multi-label Classification

2009 · Jesse Read, Bernhard Pfahringer, et al. · Lecture notes in computer science · 607

PDF

Multi-label Classification Using Ensembles of Pruned Sets

2008 · Jesse Read, Bernhard Pfahringer, et al. · Proceedings · 449

PDF

Active Learning by Querying Informative and Representative Examples

2014 · Sheng-Jun Huang, Rong Jin, et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 441

Binary relevance for multi-label learning: an overview

2017 · Min-Ling Zhang, Yu-Kun Li, et al. · Frontiers of Computer Science · 435

Multi-label learning by exploiting label dependency

2010 · Min-Ling Zhang, Kun Zhang · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 419

Multi-Label Learning with Global and Local Label Correlation

2017 · Yue Zhu, James T. Kwok, et al. · IEEE Transactions on Knowledge and Data Engineering · 414

PDF

Combining instance-based learning and logistic regression for multilabel classification

2009 · Weiwei Cheng, Eyke Hüllermeier · Machine Learning · 403

PDF

Manifold regularized discriminative feature selection for multi-label learning

2019 · Jia Zhang, Zhiming Luo, et al. · Pattern Recognition · 369

Predicting protein functions using incomplete hierarchical labels

2015 · Guoxian Yu, Hailong Zhu, et al. · BMC Bioinformatics · 360

PDF

SGM: Sequence Generation Model for Multi-label Classification

2018 · Yang, Pengcheng, Sun, Xu, et al. · arXiv (Cornell University) · 310

PDF

Labels can override perceptual categories in early infancy

2007 · Kim Plunkett, Jon-Fan Hu, et al. · Cognition · 290

Learning to diagnose from scratch by exploiting dependencies among labels

2017 · Yao, Li, Poblenz, Eric, et al. · arXiv (Cornell University) · 289

PDF

Multilabel Classification with Principal Label Space Transformation

2012 · Farbound Tai, Hsuan-Tien Lin · Neural Computation · 274

Feature selection using bare-bones particle swarm optimization with mutual information

2020 · Xian-fang Song, Yong Zhang, et al. · Pattern Recognition · 266

Ensemble application of convolutional and recurrent neural networks for multi-label text categorization

2017 · Guibin Chen, Deheng Ye, et al. · 264

Hypergraph spectral learning for multi-label classification

2008 · Liang Sun, Shuiwang Ji, et al. · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 261

Learning Label-Specific Features and Class-Dependent Labels for Multi-Label Classification

2016 · Jun Huang, Guorong Li, et al. · IEEE Transactions on Knowledge and Data Engineering · 252

Multi-Label Learning by Exploiting Label Correlations Locally

2021 · Sheng-Jun Huang, Zhi-Hua Zhou · Proceedings of the AAAI Conference on Artificial Intelligence · 249

PDF

Binary relevance efficacy for multilabel classification

2012 · Oscar Luaces, Jorge Díez, et al. · Progress in Artificial Intelligence · 245

PDF

Combining Instance-Based Learning and Logistic Regression for Multilabel Classification

2009 · Weiwei Cheng, Eyke Hüllermeier · Lecture notes in computer science · 238

Multi-label informed latent semantic indexing

2005 · Kai Yu, Shipeng Yu, et al. · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · 238

2006 · Feng Kang, Rong Jin, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 230

Active Learning by Querying Informative and Representative Examples

2010 · Sheng-Jun Huang, Rong Jin, et al. · 224

Works count: 1,585

Citation count: 35,880