New methods

[glemaitre]

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-SMOTE New methods #105 (comment)
• Cluster Based Oversampling New methods #105 (comment)
• Supervised Over-Sampling New methods #105 (comment)

Prototype Generation/Selection:

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

Ensemble

• Over-Bagging FEA allow any resampler in the BalancedBaggingClassifier #808
• Under-Bagging FEA allow any resampler in the BalancedBaggingClassifier #808
• Under-Over-Bagging FEA allow any resampler in the BalancedBaggingClassifier #808
• SMOTE-Bagging FEA 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).

[glemaitre]

@dvro @chkoar you can add anything there. We can make a PR to add these stuff in the todo list.

We should also discuss where these methods will be added (under-/over-sampling or new module)

[chkoar]

SGP it should be placed in a new module/package like in scikit-protopy. generation is a reasonable name for this kind of algorithm.

[glemaitre]

@chkoar What would be the reason to disassociate over-sampling and generation?

[chkoar]

Actually none. Just for semantic reasons. Obviously, prototype generation methods could be considered as over-sampling methods.

[dvro]

@glemaitre actually, oversampling is different than prototype generation:

Prototype Selection:
given a set of samples S, a PS method selects a subset S', where S' \in S and |S'| < |S|
Prototype Generation:
given a set of samples S, a PG method generates a new set S', where |S'| < |S|.
Oversampling:
given a set of samples S, an OS method generates a new set S', where |S'| > |S| and S \in S'

[chkoar]

Thanks for the clarification @dvro. That could be placed in the wiki!