About this add-in
This add-in is an add-in for performing Bayesian optimization using the Gaussian process model of JMP.
System requirements
- JMP 15 or later
- Display language is English and Japanese only
About Bayesian optimization
Bayesian optimization is one of the methods used to find the optimal solution by repeating successive experiments. The main flow of Bayesian optimization is as follows.
- Make a Space Filling plan (or another plan) with an appropriate number of experiments.
- do an experiment.
- The Gaussian process model is estimated from the obtained data.
- From the Gaussian process model g (x) (and its covariance matrix ∑) estimated from the data, find the point x * where A (g (x)) calculated from the appropriate function A (.) Is maximized.
- Add x * as an experimental point and return to ii.
For details on Bayesian optimization, refer to the following papers.
B. Shahriari, K. Swersky, Z. Wang, R. P. Adams and N. de Freitas, "Taking the Human Out of the Loop: A Review of Bayesian Optimization," in Proceedings of the IEEE, vol. 104, no. 1, pp. 148-175, Jan. 2016, doi: 10.1109 / JPROC.2015.2494218.
How to use the add-in
(See also the attached document)
- Open the JMP data table with the experimental data you have already entered. * Note: The current add-in supports only when the objective variable Y is one. Also, the explanatory variable X can only be a continuous scale.
- Select Add-ins> Bayesian Optimization.
- Set columns and options.
- When the analysis is finished, the result window will be displayed. If you want to add candidate experimental points to the table, click the Add Row to Table button.
- If you want to do the following experiment, you can run Bayesian optimization under the same conditions by running the table script "Run Bayesian Optimization Add-in".
screenshot
How to use this add-in
This add-in allows you to perform Bayesian optimization using Gaussian process model in JMP.
Bayesian optimization is one technique used when repeatedly performing sequential experiments and searching for an optimal solution.
Before conducting a real experiment, it is highly recommended to check whether it works well with some pseudo data. There are cases where it is impossible to find the optimal point well with few experiments.
- Open the JMP data table where you entered the experimental data you have already done.
- Select Add-Ins> Bayesian Optimization.
- Set columns and options.
- When the analysis is finished, a window will be displayed. If you want to add candidate experimental points to the table, click the “Add the row to table” button.
- If you want to repeat the Bayesian optimization, click “Run Bayesian Optimization Add-in” in the table script.
For more information, please see the attached pdf file.
