How to calculate decision weights in Decision node SAS Miner

[msf2021]

Hi everyone,

I am learning how to use oversampling methods in SAS Miner and I am using this tutorial : https://documentation.sas.com/doc/en/emref/14.3/p0ak10c0ywr8mrn1an7tum03sp7g.htm#p1exm858amo9ren1k17...

I completly understant when to use the decisions node and what the priors are but when they explain how to fill the decision weights, i don't understand how they calculate the inverse prior:

"enter the decision weights as shown in the figure above. For level GOOD, column DECISION1, enter the inverse prior value for the original proportion (0.05) of rare events: 1.0526. For level BAD, column DECISION2, enter the inverse value prior for the original proportion (0.95) of non-events: 20.0. All other values in the matrix should be 0.0. Click OK. Now your Decisions node is configured."

Can someone help me here?

[sbxkoenk]

Hello,

Using inverse priors in a profit matrix yields the central cutoff: cutoff = prior1.

The central cutoff maximizes the sum of SE and SP -- a good thing, and a good choice. 

SE = Sensitivity

SP = Specificity

Kind regards,

Koen