Hi All,
I want to build a response model but with a very low response rate, around 0.2%. I haven't built any model with such low response in the past, so I don't know what's the best way to proceed in this case with SAS Enterprise Miner. I understand the idea of oversampling but as I haven't applied it in the past, your help would be much appreciated. Once you have built the model using oversampling, how do you undo the oversampling? And at the time of scoring new data, which probabilities do we use? The one build on oversampled data or the original??
Is the Oversampling technique recommended? When is it compulsory to use it?
Many Thanks
Alice
moved to the Data Mining community where I hope you will get many great responses
I came across a decent blog post about oversampling. Perhaps it contains some answers you seek. http://www.data-mining-blog.com/tips-and-tutorials/overrepresentation-oversampling/
Also check out any links within the post.
Hi, Kanyange,
Here is a link that has video that addresses oversampling with EM
34270 - Oversampling techniques in SAS® Enterprise Miner(tm)
Another SAS note provides step-by-step instruction
24205 - Rare event oversampling for model fitting in SAS® Enterprise Miner(tm)
Enjoy. Post back if you have questions.
Best
Jason Xin
Don't miss out on SAS Innovate - Register now for the FREE Livestream!
Can't make it to Vegas? No problem! Watch our general sessions LIVE or on-demand starting April 17th. Hear from SAS execs, best-selling author Adam Grant, Hot Ones host Sean Evans, top tech journalist Kara Swisher, AI expert Cassie Kozyrkov, and the mind-blowing dance crew iLuminate! Plus, get access to over 20 breakout sessions.
Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.
Find more tutorials on the SAS Users YouTube channel.