A customer has asked me about a bayesian optimization. Does anyone has asked a similar request from a customer?
In general, Bayesian optimization is a sequential design strategy for global optimization of black-box functions that does not assume any functional forms. This method has been used to tune machine learning models. Bayesian optimization has also been recently applied in the manufacturing industry (for simulation experiments and actual experiments).
My customer wants to select the best candidate experiment for the next run based on the previous experiment's data.
Here is an example of an application for the chemical experiment.
https://www.nature.com/articles/s41586-021-03213-y
I think JMP can create a gaussian process model so that a customer could do some steps in Bayesian optimization in JMP.
Yuichi
