What inspired this Wish List Request?
The current JMP Pro 19's Bayesian Optimization generates factor setting values with too high precision (For example, 1.54321245). In real experiments, experimenters usually sets rounded values (like 1.54).
Please describe the new or improved feature or solution you would like to see.
The factor settins are rounded (For example, 1.54 instead of 1.54321245).
What would the value be to you and/or other users if this new feature is provided?
If this feature is implemented, users will not need to round factor setting values before theri experiments.
Is this an external customer request?
Yes. This is a request by a JMP Pro user at Astellas Pharma. We got this his request when I offered the on-line seminar for JMP Pro 19's Bayesian Optimization on Oct-08-2025. They are already JMP Pro users.
He asked us that an option to round factor setting values in candidate data sets and proposed combinations. For example, JMP Pro 19's Bayesian Optimization outputs x1 = 1.2591345, x2=2451.345, but they actually do experiment with x1=1.26 and x2=2450. (We will answer to him that (a) you need to round off afeter you save the values in data tables, or (b) you need to prepare a data table of candidate sets in which values are rounded.
I am not sure how we can implement this feature. One solution might be to offer a option to see the format of each X column in a data table, and use the format for rounding (For example, if the format for x1 is Fixed Dec (8,2), values are rounded to 2 digits (like 1.26)).
Is there a competitive software package that has this feature or solution that we should be aware of? I do not know.
Will this impact a renewal, expansion, or adoption at a customer, and does this put an account at risk if we do not address this?
The user is already JMP Pro user. I do not know what they will do if JMP Pro does not have this feature.
