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Jun 15, 2017 2:58 PM
(375 views)

Hi,

I'm using JMP pro to create models of some process data that include 11 factors and a response. What I would like to do is predict the value of the response with a confidence interval (or similar statistic) based on specific values of the factors. This is possible to do with the prediction profiler using linear models under the fit model platform.

The problem is that the neural network model seems to do much better than others with this data and when I fix the values of the factors, I get a predicted response value with no statistic on how accurate this prediction is (like the confidence intervals in the fit model platform). Is there a way to get more information on this prediction? Thanks.

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Jun 16, 2017 10:48 AM
(360 views)

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Jun 16, 2017 12:03 PM
(353 views)

Thanks. That looks great. Is there a way to get these with the standard error or standard deviation into a profiler? Or is the only way to make future predictions of response is by entering factor values in a new row in the table and checking the result?

I'm asking because I'll have to share the results within the company and am trying to figure out the best way to do this. I know the profiler can be saved as html.

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Jun 19, 2017 2:48 AM
(330 views)

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Jun 19, 2017 3:31 AM
(327 views)