Hi,
First of all, there is no over-sampling node in EM. I figure you meant Sample Node. The Sample Node has random, systematic, First, N, stratify... None of them allows you to change the ration between 1 and 0 on the target. The purpose of sampling is to take a subset, in one way or another, to represent the master source. The goal is to represent, not to alter. On the other hand, the matter of oversampling is to recompose a sample, therefore to alter, logically. Sampling Node often is used in situation like : The qualified model universe has 20 million observations. I need to take 5% sample to make it work in EM. In this sense, sampling really is not analytical/technical. But oversampling is every bit of analytics. In other words, the reason you run sampling should not overlap with that driving oversampling, although the act of oversampling per SE is sampling. Hope this helps? Thank you for using SAS. Best. Jason Xin
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