Scott Allen, Sr Systems Engineer, JMP
JMP Pro’s Neural Network platform provides a powerful and flexible tool for generating predictive models for many types of data. Users optimize the models by adjusting various parameters and then compare individual models within the platform. This process is carried out manually, however, which takes a significant amount of user interaction and may not necessarily uncover an optimal model.
This presentation demonstrates the use of a JMP Pro add-in designed to screen neural network tuning parameters. The add-in creates a fast, flexible space-filling design based on user input, then runs a neural network model for each set of parameters. A graphical report helps users identify optimal models, so they can then run the selected model(s) or continue tuning the parameters to build their understanding of the system. Finally, the add-in allows users to save the results from the tuning optimization and return to it later, which is helpful when dealing with omplex neural network models that might take considerable computing time.
Various JMP customers and Community members have inquired about a neural network tuning capability in JMP; this feedback was used to guide the development of this add-in. Prior to Discovery Summit, the add-in will be posted to the Community with a blog post containing documentation notes and guidance on using the add-in.
