Demystifying the Bayesian Optimization Platform in JMP Pro (2026-US-30MP-2942)

While the JMP Bayesian Optimization platform’s Auto Mode conveniently automates the sequential experimentation process for the most common applications, working directly with candidate sets and the Augmented Acquisition Functions Profiler in Custom Mode opens the possibility of more user-driven Bayesian optimization.

We explain the meaning of the different acquisition functions, along with how and when to use them, empowering you to get the most of the Bayes Optimization platform for creative problem solving. Developers answer users' common questions, such as how to create a starting design, how many runs it should have, how to choose a batch size, how to create custom candidate sets to handle unusual constraints (such as patent avoidance), changing factor ranges, and handling hard to change factors. We show examples that illustrate creative use of candidate sets to solve problems to show you how to handle complex constraints.