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Keyword

binary relevance

Description: A multilabel classification method that trains a separate binary classifier to predict each label independently.
OpenAlex ID: keywords/binary-relevance
Classifier chains for multi-label classification
2011 · Jesse Read, Bernhard Pfahringer, et al. · Machine Learning · 2,293
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An extensive experimental comparison of methods for multi-label learning
2012 · Gjorgji Madjarov, Dragi Kocev, et al. · Pattern Recognition · 727
Classifier Chains for Multi-label Classification
2009 · Jesse Read, Bernhard Pfahringer, et al. · Lecture notes in computer science · 607
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Binary relevance for multi-label learning: an overview
2017 · Min-Ling Zhang, Yu-Kun Li, et al. · Frontiers of Computer Science · 435
Multilabel Classification with Principal Label Space Transformation
2012 · Farbound Tai, Hsuan-Tien Lin · Neural Computation · 274
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
Binary relevance efficacy for multilabel classification
2012 · Oscar Luaces, Jorge Díez, et al. · Progress in Artificial Intelligence · 245
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Multi-label Hate Speech and Abusive Language Detection in Indonesian Twitter
2019 · Muhammad Okky Ibrohim, Indra Budi · 243
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An Empirical Study of Lazy Multilabel Classification Algorithms
2008 · E. Spyromitros, G. Tsoumakas, et al. · Lecture notes in computer science · 233
Learning Label Specific Features for Multi-label Classification
2015 · Jun Huang, Guorong Li, et al. · Proceedings · 194
Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain
2008 · Eneldo Loza Mencía, Johannes Fürnkranz · Lecture notes in computer science · 152
A network approach to the systematic analysis of yeast gene function
1996 · Stephen Oliver · Trends in Genetics · 132
An empirical evaluation of supervised learning approaches in assigning diagnosis codes to electronic medical records
2015 · Ramakanth Kavuluru, Anthony Rios, et al. · Artificial Intelligence in Medicine · 124
Correlation-Based Pruning of Stacked Binary Relevance Models for Multi-Label Learning
2009 · Grigorios Tsoumakas, Anastasios Dimou, et al. · 117
A Study on Threshold Selection for Multi-label Classification
2007 · Rong-En Fan, Chih‐Jen Lin · 117
Joint Ranking SVM and Binary Relevance with robust Low-rank learning for multi-label classification
2019 · Guoqiang Wu, Ruobing Zheng, et al. · Neural Networks · 116
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Incorporating label dependency into the binary relevance framework for multi-label classification
2011 · Everton Alvares-Cherman, Jean Metz, et al. · Expert Systems with Applications · 107
Binary and graded relevance in IR evaluations—Comparison of the effects on ranking of IR systems
2005 · Jaana Kekäläinen · Information Processing & Management · 100
Ensemble extreme learning machines for compound-fault diagnosis of rotating machinery
2019 · Xian-Bo Wang, Xiaoyuan Zhang, et al. · Knowledge-Based Systems · 97
An Analysis of the Softmax Cross Entropy Loss for Learning-to-Rank with Binary Relevance
2019 · Sebastian Bruch, Xuanhui Wang, et al. · ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR) · 96
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A survey on multi-label feature selection from perspectives of label fusion
2023 · Wenbin Qian, Jintao Huang, et al. · Information Fusion · 87
Multi-label learning for crop leaf diseases recognition and severity estimation based on convolutional neural networks
2020 · Miaomiao Ji, Keke Zhang, et al. · Soft Computing · 74
Multi-label Arabic text categorization: A benchmark and baseline comparison of multi-label learning algorithms
2018 · Bassam Al-Salemi, Masri Ayob, et al. · Information Processing & Management · 72
A Machine Learning-Based Recommender System for Improving Students Learning Experiences
2020 · Nacim Yanes, Ayman Mohamed Mostafa, et al. · IEEE Access · 70
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Performance comparison of multi-label learning algorithms on clinical data for chronic diseases
2015 · Damien Zufferey, Thomas Hofer, et al. · Computers in Biology and Medicine · 68
Works count: 505
Citation count: 10,540
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