https://datascienceschool.net/view-notebook/c1a8dad913f74811ae8eef5d3bedc0c3/
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* Solution
- Re-up-sampling
- Re-down-sampling
- Combining up and down sampling
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* Re-down-sampling
- RandomUnderSampler: random under-sampling method
- TomekLinks: Tomek’s link method
- CondensedNearestNeighbour: condensed nearest neighbour method
- OneSidedSelection: under-sampling based on one-sided selection method
- EditedNearestNeighbours: edited nearest neighbour method
- NeighbourhoodCleaningRule: neighbourhood cleaning rule
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* Re-up-sampling
- RandomOverSampler: random sampler
- ADASYN: Adaptive Synthetic Sampling Approach for Imbalanced Learning
- SMOTE: Synthetic Minority Over-sampling Technique
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* Combining up and down sampling
- SMOTEENN: SMOTE + ENN
- SMOTETomek: SMOTE + Tomek
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