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Solve problems, and share tips and tricks with other JMP users.
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frankderuyck
Level VII

Problem to find optimal settings for a mixture with Bayesian Optimisation

With a 24 run mixture DOE I could find very good models and optimal settings for a ternary mixture and one categorical effect, this was presented in foregoing discussion; find in attachment again the analysis and below screenshots of the desirability results. 

frankderuyck_0-1788534496337.png

With Isomer 2 desirability result is worse; below the settings when locking Isomer 2

frankderuyck_1-1788534633931.png

Starting with a 9 run candidate space filling set (see attachment Succesful 9 run) set or a 12 run Kowalski set the optimal settings with Isomer 1 can be detected. 

However starting from a 6 run space filling candidate set I always get the poorer optimal settings with Isomer 2, even after several added space filling runs! What did I do wrong and how to get from this 6 run candidate the optimal Isomer 1 settings? 

14 REPLIES 14
frankderuyck
Level VII

Re: Problem to find optimal settings for a mixture with Bayesian Optimisation

No succes after double Max Multimodel Std Dev, low desirability at Isomer 1 and BO goes back to Isomer 2

Victor_G
Super User

Re: Problem to find optimal settings for a mixture with Bayesian Optimisation

Frank, please start ONLY with your 6 initial space filling runs, without any BO scripts in the table (remove the scripts and delete any other rows).
Then, launch the BayesOpt platform with default settings, remove any automatic batch recommendation and add 1 Max Multimodel Std Dev for 2 iterations, and you should be able to get results close to your optimum with isomer 1 (and matching my testings). As soon as the two consecutive Max Multimodel Std Dev runs have been added, you should see a correct ordering of the isomer types :

Victor_G_0-1788783078290.png

 

 

Victor GUILLER

"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)
frankderuyck
Level VII

Re: Problem to find optimal settings for a mixture with Bayesian Optimisation

Hi Victor, I followed your instructions cfr. attachment and I can't replicate your resuts? The models built with the 6 initial space filling rus are poor so I don't understand why to sart here with Max Multimodel st deviation: the outcomes are not learning a lot from poor Gaussian Process models?

frankderuyck
Level VII

Re: Problem to find optimal settings for a mixture with Bayesian Optimisation

In your result you have only 2 outputs; there must be three

frankderuyck
Level VII

Re: Problem to find optimal settings for a mixture with Bayesian Optimisation

And after only 6 initial space filling runs Gaussian Y1 is very poor so additional space filling runs are required to get acceptable model performance;  unfortunately, each time again, BO detects isomer 2 as optimal (?)

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