Hi,
I have a dataset (30k) with event = 82% and non-event = 18%, is this still possible to use normal way to model (ie. neural/regression/etc)? So far, i dont' have a good result yet (DT, regression, scorecard, 50/50 oversampling, Neural was used). Or should i try to reverse the Event to 18% and build a model for that?
18%/82% is actually a good split in my experience.
Why do you think you don't have a good fit?
All the models give me a very unstable lift chart with a lift of 1.10 at most. I am still trying out with different segments, but this will only reduce my 30k to a smaller size, which i am trying to avoid.
This is what Data Mining should be if you don't have a big table. Why not try PROC LOGISTIC ,since your table is quite small .
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