https://datascienceschool.net/view-notebook/c1a8dad913f74811ae8eef5d3bedc0c3/ ================================================================================ * Solution - Re-up-sampling - Re-down-sampling - Combining up and down sampling ================================================================================ * 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 ================================================================================ * Re-up-sampling - RandomOverSampler: random sampler - ADASYN: Adaptive Synthetic Sampling Approach for Imbalanced Learning - SMOTE: Synthetic Minority Over-sampling Technique ================================================================================ * Combining up and down sampling - SMOTEENN: SMOTE + ENN - SMOTETomek: SMOTE + Tomek ================================================================================