SMOTE
Synthetic Minority Over-sampling Technique.
Perhaps the most widely used approach to synthesizing new examples is called the Synthetic Minority Oversampling Technique, or SMOTE for short. This technique was described by Nitesh Chawla, et al. in their 2002 paper named for the technique titled “SMOTE: Synthetic Minority Over-sampling Technique.”

SMOTE works by selecting examples that are close in the feature space, drawing a line between the examples in the feature space and drawing a new sample at a point along that line.
SMOTE: Synthetic Minority Over-sampling Technique
https://paperswithcode.com/paper/smote-synthetic-minority-over-sampling
SMOTE: Synthetic Minority Over-sampling Technique