Bayesian Optimization, aka BayesOpt, is a new platform coming to JMP Pro 19. With it, you can use your existing data to fit a model and then use that model to intelligently decide where to sample next. These new observations are used to update the model and find even better samples. This process can start with a minimal number of runs, which means wasting fewer resources on suboptimal samples and spending more time exploring new opportunities.
More resources:
- Developer Tutorial: https://community.jmp.com/t5/Learn-JMP-Events/Developer-Tutorial-Bayesian-Optimization/ev-p/894910
- JMP Cable Article: https://community.jmp.com/t5/JMPer-Cable/Introducing-the-Bayesian-Optimization-platform-in-JMP-Pro/b...
