Survey of resampling techniques for improving classification performance in unbalanced datasets

Asymptotic properties of nearest neighbor rules using edited data

Dennis L Wilson · 1972

Earlier work this paper cites.

Two modifications of cnn

Ivan Tomek · 1976

Earlier work this paper cites.

Addressing the curse of imbalanced training sets: one-sided selection

Miroslav Kubat, Stan Matwin, et al · 1997

Earlier work this paper cites.

Logistic regression in rare events data

Gary King and Langche Zeng · 2001

Earlier work this paper cites.

Smote: synthetic minority over-sampling technique

Nitesh V. Chawla, Kevin W. Bowyer, Lawrence O. Hall, and W. Philip Kegelmeyer · 2002

Earlier work this paper cites.

Smoteboost: Improving prediction of the minority class in boosting

Nitesh V Chawla, Aleksandar Lazarevic, Lawrence O Hall, and Kevin W Bowyer · 2003

Cited alongside, same era.

knn approach to unbalanced data distributions: a case study involving information extraction

Inderjeet Mani and I Zhang · 2003

Cited alongside, same era.

Class imbalances versus small disjuncts

Taeho Jo and Nathalie Japkowicz · 2004

Cited alongside, same era.

Borderline-smote: a new over-sampling method in imbalanced data sets learning

Hui Han, Wen-Yuan Wang, and Bing-Huan Mao · 2005

Cited alongside, same era.

The condensed nearest neighbor rule (corresp.)

P. Hart · 2006

Cited alongside, same era.

Adasyn: Adaptive synthetic sampling approach for imbalanced learning

Haibo He, Yang Bai, Edwardo A Garcia, and Shutao Li · 2008

Later among the works it cites.

Learning from imbalanced data

Haibo He and Edwardo A Garcia · 2009

Later among the works it cites.

Exploratory undersampling for class-imbalance learning

Xu-Ying Liu, Jianxin Wu, and Zhi-Hua Zhou · 2009

Later among the works it cites.

Borderline over-sampling for imbalanced data classification

Hien M Nguyen, Eric W Cooper, and Katsuari Kamei · 2011

Later among the works it cites.