User Community
cancel
Turn on suggestions
Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.
Showing results for 
Show  only  | Search instead for 
Did you mean: 
  • 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.
JMP Bar Chart

Welcome to the JMP User Community!

Ask questions, get answers, meet other JMP users

Learning Resources

Find courses, tutorials, and lots of other methods of learning JMP.

view all learning resources

Latest Discussions

  • K fold

    Hi!How can I perform a KFold cross-validation with neural networks model by using JMP 15.1?.
    Thanks in advance!

    Marlly_Guarin Marlly_Guarin
    Discussions |
    Jun 2, 2020 10:10 AM
    2002 views | 1 replies

  • How do I auto-calculate precision and F1 score for models on imbalanced data?

    I like that JMP's prints a confusion matrix and ROC for the logistic (Generalized) regression, but some important metrics seem to be missing from the results: precision and F1 score. Is there a way to auto-include these in the output? Or, have it be computed as "automatically" as possible when I re-run a new classificaiton model. I am trying to avoid manually recomputing these with each new model....

    Oleg Oleg
    Discussions |
    Sep 28, 2017 3:40 PM
    20680 views | 16 replies

Latest Discussions

  • How do I auto-calculate precision and F1 score for models on imbalanced data?

    I like that JMP's prints a confusion matrix and ROC for the logistic (Generalized) regression, but some important metrics seem to be missing from the results: precision and F1 score. Is there a way to auto-include these in the output? Or, have it be computed as "automatically" as possible when I re-run a new classificaiton model. I am trying to avoid manually recomputing these with each new model....

    Oleg Oleg
    Discussions |
    Sep 28, 2017 3:40 PM
    20680 views | 16 replies

Latest Discussions

Nothing posted at the moment.

view all discussions

JMP Events

Sorrento, Italy 10-12 March
view all events
Latest Blog Post

Revolutionizing Spectral Baseline Correction in JMP: Harness the Power of Python Integration

JMP blog post photo
view all blog articles

Learn more about JMP's premier analytics conference