After oversampling/undersampling is it always appropriate to adjust probabilities using the odds ratio regardless of the sampling method used?

  1. I have an imbalanced dataset where the target class is <1% of sample.
  2. I apply oversampling or undersampling e.g. https://github.com/scikit-learn-contrib/imbalanced-learn.
  3. I run random forest on the resampled data
  4. I adjust probabilities back to the original sample by multiplying by the ratio of odds ratios as explained here: https://yiminwu.wordpress.com/2013/12/03/how-to-undo-oversampling-explained/

Is step 4 always the same regardless of the type of oversampling or undersampling employed?

Answer

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Source : Link , Question Author : simon , Answer Author : Community

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