2001, Knowledge Discovery, Measurement and Testing

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

MAY 20, 2021

This renders measures like classification accuracy meaningless. Their tests are performed using C4.5-generated note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). The use of multiple measurements in taxonomic problems. Chawla et al.,

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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