Optimal way to use model previously fitted in HPLOGISTIC to score new dataset

[clarkchong1]

I am using SAS 9.4. The documentation for HPLOGISTIC said that its focus were to fit and score large datasets. I am wondering what is the optimal to use it to

a) fit a model

b) then use the model to score some future datasets

I could think of at least two ways:

i) use OUTEST option then capture the parameter output with ODS, then use INEST with 0 iteration in a future LOGISTIC / HPLOGISTIC statement

ii) use the CODE option to generate the code for future scoring

Which one is more preferred? Or is there a better third way? Thank you!

[Rick_SAS · Accepted solution]

For an overview of the various methods, see "Techniques for scoring a regression model in SAS." Which you use is largely a matter of taste. The CODE method is slightly more complicated to deploy, but is often used on Big Data problems because you can the DATA step is so fast, or even run DS2 code in parallel on a grid.