Hi ,
Can someone please suggest when we do oversampling ,do we do this on main dataset and then we spilt it into Training and Validation (so both are over sampled)? Or we first make Training and Validation datasets nd then oversample Training dataset and perform validation on non-oversampled Validation dataset? Thanks.
I don't see the need for unequal probability sub-sampling for the validation data. By keeping the original event probability in the validation dataset you could also check that your weighting in the training data was done properly.
Note : I edited the topic title to attract attention from others to this question.
Oversampling for what purpose? Bootstrap?
I don't see the need for unequal probability sub-sampling for the validation data. By keeping the original event probability in the validation dataset you could also check that your weighting in the training data was done properly.
Note : I edited the topic title to attract attention from others to this question.
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