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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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MAY 20, 2021

Insufficient training data in the minority class — In domains where data collection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large. The unreasonable effectiveness of data. Data mining for direct marketing: Problems and solutions. UCI machine learning repository.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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