2001, 2009, Knowledge Discovery and Modeling

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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MAY 20, 2021

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. References. Banko, M., & Brill, E. link] Chawla, N. UCI machine learning repository.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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