Contribution-based imbalanced hybrid resampling ensemble

SMOTE: Synthetic Minority Over-sampling Technique

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Computing, Computer Science, Data Science +12

A study of the behavior of several methods for balancing machine learning training data

Gustavo E. A. P. A. Batista, Ronaldo C. Prati, Maria Carolina Monard · ACM SIGKDD Explorations Newsletter · 2004 · 4.1K citations

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Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning

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Clustering-based undersampling in class-imbalanced data

Wei‐Chao Lin, Chih‐Fong Tsai, Ya‐Han Hu et al. · Information Sciences · 2017 · 822 citations

Computing, Computer Science, Data Science +14

SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering

José A. Sáez, Julián Luengo, Jerzy Stefanowski et al. · Information Sciences · 2014 · 619 citations

Computing, Computer Science, Machine Learning +16