ML internals: Synthetic Minority Oversampling (SMOTE) Technique
Domino Data Lab
MAY 20, 2021
In their 2002 paper Chawla et al. propose a different strategy where the minority class is over-sampled by generating synthetic examples. Figure 3 shows visual explanation of how SMOTE generates synthetic observations in this case. 2002) have performed a comprehensive evaluation of the impact of SMOTE- based up-sampling.
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