0
$\begingroup$

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.

Improve this question
$\endgroup$
2
  • $\begingroup$ You may want to check this question and this question $\endgroup$
    – noe
    Nov 10 at 10:28
  • $\begingroup$ @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. $\endgroup$
    – Full Array
    Nov 10 at 16:37

0

Reset to default

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.