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Keyword

multi-label classification

Description: A machine-learning classification task in which each instance can be assigned multiple labels, often using methods that model label relationships.
Wikidata ID: wiki/Q3553958
OpenAlex ID: keywords/multi-label-classification
Experiments with a new boosting algorithm
1996 · Yoav Freund, Robert E. Schapire · 8,210
A systematic analysis of performance measures for classification tasks
2009 · Marina Sokolova, Guy Lapalme · Information Processing & Management · 7,089
ML-KNN: A lazy learning approach to multi-label learning
2007 · Min-Ling Zhang, Zhi-Hua Zhou · Pattern Recognition · 3,554
A Review on Multi-Label Learning Algorithms
2013 · Min-Ling Zhang, Zhi-Hua Zhou · IEEE Transactions on Knowledge and Data Engineering · 3,328
Structural Deep Network Embedding
2016 · Daixin Wang, Peng Cui, et al. · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 2,844
Improved boosting algorithms using confidence-rated predictions
1998 · Robert E. Schapire, Yoram Singer · 2,552
Multi-Label Classification
2007 · Grigorios Tsoumakas, Ioannis Katakis · International Journal of Data Warehousing and Mining · 2,509
Learning multi-label scene classification
2004 · Matthew R. Boutell, Jiebo Luo, et al. · Pattern Recognition · 2,354
Classifier chains for multi-label classification
2011 · Jesse Read, Bernhard Pfahringer, et al. · Machine Learning · 2,293
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SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary
2018 · Alberto Fernandez, Salvador Garcia, et al. · Journal of Artificial Intelligence Research · 2,221
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Improved Boosting Algorithms Using Confidence-rated Predictions
1999 · Robert E. Schapire, Yoram Singer · Machine Learning · 1,971
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Mining Multi-label Data
2009 · Grigorios Tsoumakas, Ioannis Katakis, et al. · Springer eBooks · 1,467
A Kernel Method for Multi-Labelled Classification
2002 · Andre Elisseeff, Jason Weston · The MIT Press eBooks · 1,387
Evaluation metrics and statistical tests for machine learning
2024 · Oona Rainio, Jarmo Teuho, et al. · Scientific Reports · 1,304
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node2vec: Scalable Feature Learning for Networks
2016 · Grover, Aditya, Leskovec, Jure · PubMed · 1,152
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MedMNIST v2 - A large-scale lightweight benchmark for 2D and 3D biomedical image classification
2023 · Jiancheng Yang, Rui Shi, et al. · Scientific Data · 1,040
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Training deep networks for facial expression recognition with crowd-sourced label distribution
2016 · Emad Barsoum, Cha Zhang, et al. · ACM International Conference on Multimodal Interaction (ICMI) · 922
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Random k-Labelsets: An Ensemble Method for Multilabel Classification
2007 · Grigorios Tsoumakas, Ioannis Vlahavas · Lecture notes in computer science · 919
Multilabel classification via calibrated label ranking
2008 · Johannes Fürnkranz, Eyke Hüllermeier, et al. · Machine Learning · 909
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Random k-Labelsets for Multilabel Classification
2010 · Grigorios Tsoumakas, Ioannis Katakis, et al. · IEEE Transactions on Knowledge and Data Engineering · 897
Learning to Diagnose with LSTM Recurrent Neural Networks
2015 · Lipton, Zachary C., Kale, David C., et al. · arXiv (Cornell University) · 879
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Multi-Task Learning as Multi-Objective Optimization
2018 · Sener, Ozan, Koltun, Vladlen · arXiv (Cornell University) · 834
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Doctor AI: Predicting Clinical Events via Recurrent Neural Networks
2015 · Choi, Edward, Bahadori, Mohammad Taha, et al. · arXiv (Cornell University) · 792
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Knowledge Discovery in Multi-label Phenotype Data
2001 · Amanda Clare, Ross D. King · Lecture notes in computer science · 757
An extensive experimental comparison of methods for multi-label learning
2012 · Gjorgji Madjarov, Dragi Kocev, et al. · Pattern Recognition · 727
Works count: 13,960
Citation count: 245,900
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