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Keyword

cost-sensitive learning

Description: A machine-learning framework that incorporates unequal costs of errors, actions, or data acquisition into model training and decision-making.
OpenAlex ID: keywords/cost-sensitive-learning
Survey on deep learning with class imbalance
2019 · Justin M. Johnson, Taghi M. Khoshgoftaar · Journal Of Big Data · 2,999
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The foundations of cost-sensitive learning
2001 · Charles Elkan · 1,943
An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics
2013 · Victoria López, Alberto Fernández, et al. · Information Sciences · 1,592
Training cost-sensitive neural networks with methods addressing the class imbalance problem
2006 · Zhi-Hua Zhou, Xu-Ying Liu · IEEE Transactions on Knowledge and Data Engineering · 1,325
Data Mining for Imbalanced Datasets: An Overview
2009 · Nitesh V. Chawla · Springer eBooks · 1,174
Applying Support Vector Machines to Imbalanced Datasets
2004 · Rehan Akbani, Stephen Kwek, et al. · Lecture notes in computer science · 1,152
A Survey of Predictive Modeling on Imbalanced Domains
2016 · Paula Branco, Luís Torgo, et al. · ACM Computing Surveys · 1,122
Learning Deep Representation for Imbalanced Classification
2016 · Chen Huang, Yining Li, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,026
Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data
2017 · Salman H. Khan, Munawar Hayat, et al. · IEEE Transactions on Neural Networks and Learning Systems · 972
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SVMs Modeling for Highly Imbalanced Classification
2008 · Yuchun Tang, Yan-Qing Zhang, et al. · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · 970
Handling imbalanced datasets: A review
2006 · Sotiris Kotsiantis, Dimitris Kanellopoulos, et al. · 921
Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction
2003 · G. M. Weiss, F. Provost · Journal of Artificial Intelligence Research · 921
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C4.5, Class Imbalance, and Cost Sensitivity: Why Under-Sampling beats Over-Sampling
2003 · Chris Drummond, Robert C. Holte · 786
A survey on addressing high-class imbalance in big data
2018 · Joffrey L. Leevy, Taghi M. Khoshgoftaar, et al. · Journal Of Big Data · 761
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Weighted extreme learning machine for imbalance learning
2012 · Weiwei Zong, Guang-Bin Huang, et al. · Neurocomputing · 743
Cost-sensitive learning by cost-proportionate example weighting
2004 · B. Zadrozny, J. Langford, et al. · Proceedings · 680
Handling class imbalance in customer churn prediction
2008 · J. Burez, D. Van den Poel · Expert Systems with Applications · 549
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Distributed data mining in credit card fraud detection
1999 · P.K. Chan, W. Fan, et al. · IEEE Intelligent Systems and their Applications · 540
mlr: Machine Learning in R
2013 · Bernd Bischl, Michel Lang, et al. · 506
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An instance-weighting method to induce cost-sensitive trees
2002 · Kai Ming Ting · IEEE Transactions on Knowledge and Data Engineering · 504
Anomaly Detection over Noisy Data Using Learned Probability Distributions
2000 · Eskin, Eleazar · 486
Deep Transfer Learning Based Classification Model for COVID-19 Disease
2020 · Y. Pathak, P.K. Shukla, et al. · IRBM · 460
Weakly supervised learning of biomedical information extraction from curated data
2016 · Suvir Jain, Kashyap R., et al. · BMC Bioinformatics · 451
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Learning and making decisions when costs and probabilities are both unknown
2001 · Bianca Zadrozny, Charles Elkan · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 450
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Data Mining for Imbalanced Datasets: An Overview
2006 · Nitesh V. Chawla · Springer eBooks · 444
Works count: 3,380
Citation count: 74,730
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