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  • JMP will suspend normal business operations for our Winter Holiday beginning on Wednesday, Dec. 24, 2025, at 5:00 p.m. ET (2:00 p.m. ET for JMP Accounts Receivable).
    Regular business hours will resume at 9:00 a.m. EST on Friday, Jan. 2, 2026.
  • We’re retiring the File Exchange at the end of this year. The JMP Marketplace is now your destination for add-ins and extensions.

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Grizzly
Level I

Hyperparameters and neural network architecture

Hello,

I'm trying to reproduce the results obtained on JMP with the "Neural" model by adding nested cross-validation, which is not possible on the software. However, the architecture is very unclear and I can't understand the calculations performed by the model. I don't have access to certain information such as batch size, optimizer used, loss, learning rate (except the one for the boosting), and any other method or penalization used.
How could I possibly have access to this information? Without it, my results obtained on JMP would be unusable as they would not be reproducible...

Thank you in advance for your reply!

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