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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

MAY 20, 2021

Machine Learning algorithms often need to handle highly-imbalanced datasets. propose a different strategy where the minority class is over-sampled by generating synthetic examples. A weighted nearest neighbor algorithm for learning with symbolic features. Machine Learning, 57–78. References. link] Halevy, A.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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