This is a non exhaustive list of the methods that can be added for the next release.

Oversampling:

• SPIDER
• MWMOTE
• SMOTE-SL
• SMOTE-RSB
• SMOTE-NC
• Random-SMOTENew methods #105 (comment)
• Cluster Based OversamplingNew methods #105 (comment)
• Supervised Over-SamplingNew methods #105 (comment)

Prototype Generation/Selection:

• Steady State Memetic Algorithm (SSMA)
• Adaptive Self-Generating Prototypes (ASGP)

Ensemble

• Over-BaggingFEA allow any resampler in the BalancedBaggingClassifier #808
• Under-BaggingFEA allow any resampler in the BalancedBaggingClassifier #808
• Under-Over-BaggingFEA allow any resampler in the BalancedBaggingClassifier #808
• SMOTE-BaggingFEA allow any resampler in the BalancedBaggingClassifier #808
• RUS-Boost
• SMOTE-Boost
• RAMO-Boost
• EUS-Boost

Regression

• SMOTE for regression

P. Branco, L. Torgo and R. Ribeiro (2016). A Survey of Predictive Modeling on Imbalanced Domains. ACM Comput. Surv. 49, 2, 31. DOI:http://dx.doi.org/10.1145/2907070

Branco, P. and Torgo, L. and Ribeiro R.P. (2017) "Pre-processing Approaches for Imbalanced Distributions in Regression" Special Issue on Learning in the Presence of Class Imbalance and Concept Drift. Neurocomputing Journal. (submitted).