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
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%20explainable%20AI%20with%20Shapley%20values.html
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%20Kernel%20SHAP.html
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!
