Sampling algorithms to aid classifiers in learning from two-class imbalanced data sets. Over-sampling, under-sampling, and hybrid algorithms are included. In addition, sampling algorithms that are composed of a sequence of already existing algorithms can be easily created.
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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