Integrating JMP PRO Python Model (NN) with explainable AI SHAP values

[#1]

Has anyone successfully connected an integration process in python to take a JMP PRO generated model ( NN ) for example and attempted to run SHAP values on the model? 

Any ideas or python code to help get across the line would be greatly appreciated. 

Here is some great documentation on SHAP 
https://shap.readthedocs.io/en/latest/example_notebooks/overviews/An%20introduction%20to%20explainab...

SHAP is model agnostic, I am just trying to figure out the specific code to incorporate JMP Generated models into

shap.KernelExplainer

function :more here https://shap.readthedocs.io/en/latest/example_notebooks/tabular_examples/model_agnostic/Simple%20Ker...

SAS VIYA has it already integrated in the software, so I am optimistic we can figure out a solution to get it incorporated into JMP at some point as an add-in.

https://www.sas.com/content/dam/SAS/support/en/sas-global-forum-proceedings/2020/4502-2020.pdf

Thank you! 

[#2]

Hi @Sizemokj Beginning in JMP Pro v.17, Shapley values are available as an option in the prediction profiler.

https://www.jmp.com/support/help/en/17.0/#page/jmp/prediction-profiler-options.shtml