Discontinuous design space


I am working on an optimisation in a highly non-linear design space.
The idea is to create a surrogate model with least samples possible. I have 200 samples for now, there are 16 design parameters and 1 quantity of interest.
What would you recommend me to try from your code?


BTW I put my DOE table here in the case you want to check it out.

Hi @lukav, have you tried fitting a standard least squares / compressed sensing / elastic-net polynomial to your data? You can start with order one and then perhaps try order two. Cheers!