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I am seriously curious on how imbalance data was treated in machine learning and statistical learning before modern time data augmentation solutions such as SMOTE appeared.

Please provide citations not only opinions.

Full Array
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  • You may want to check this question and this question – noe Nov 10 '23 at 10:28
  • @noe Thanks for the input and time. Much appreciated. I was aware of bias introduced by data augmentation techniques thus the origin of my question above. I will leave the question open because I need to know how the ML community trained vintage (before data augmentation) ML models on imbalance data. – Full Array Nov 10 '23 at 16:37

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