2001, Knowledge Discovery, Measurement and Strategy

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

MAY 20, 2021

This renders measures like classification accuracy meaningless. propose a different strategy where the minority class is over-sampled by generating synthetic examples. The use of multiple measurements in taxonomic problems. The class imbalance problem: Significance and strategies. In their 2002 paper Chawla et al.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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