Hi, I have a heavily imbalanced dataset with the rare target level at around 1% (binary variable) and I have 20000 observations in my training set (200 rare events). I need to get a sample with ~40000 observations where 50% of them are the rare event. I tried to use the sample node and do the standard oversampling in enterprise miner (see screenshot) as described here https://support.sas.com/kb/24/205.html
But all I get is a sample of 400 with the original 200 rare events so it is basically doing undersampling rather than
oversampling...
I would also like to use SMOTE rather than simple duplications but I do not see the option on Enterprise Miner. I checked all the other posts on SMOTE including all the links here https://communities.sas.com/t5/Statistical-Procedures/Assistance-with-SAS-code-for-SMOTE-and-adaptiv... but the sample SAS codes are difficult to understand and apply.
Can anybody help me with these two issues?
PS. My dataset contains both numeric and character input (predictor) variables.
Oversampling is a misnomer. It is actually undersampling as you've experienced.
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