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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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Latest Discussions

  • Want to run the same tuning design table for multiple y-variables

    I'm running bootstrap forest as a predicative model. I have hyperparameters I like but want to run multiple times (ex. 500 replicates) to find the random forest that gives me the best validation r square. I have the tuning design table built, but every time it runs for one predicted y-variable (there are 11 in my dataset) I have to manually choose the same design table every time. It's time consum...

    ClassCanary405 ClassCanary405
    Discussions |
    Oct 16, 2023 2:37 AM
    1165 views | 2 replies
  • Adding new data using previously develop random forest model

    Community,I am working with my colleague Kim on a project she used random forest to develop a prediction model for plant disease in potato based on soil properties. Here are our questions: How do we use new data with the already generated model that was already validated?How can we validate that the old predictive model is explaining the response variable?The predictive model indicates that with h...

    anaheilman anaheilman
    Discussions |
    Oct 13, 2023 11:30 AM
    1300 views | 1 replies
  • How to screen easily the non significant of many factors(~200 columns) before to perform a mulitple regression.

    I have many factor (~200 columns) and one response,i have many measures.Most of this factors show colinearity between them,is there a simple way to perform a first filter of the not relevant factors?Then in the remaining i will perform a multiple regression.

    Perpignan_italy Perpignan_italy
    Discussions |
    Oct 10, 2023 5:50 AM
    2084 views | 3 replies
  • I want to validate the decision tree with different data.

    I am studying medical statistics in Japan, sorry if there are any problems with English.
    We are using JMP pro Ver 17.1.0.
    We have created a prediction model with data from Facility A using the JMP partition.
    I would like to examine how accurately this model classifies and predicts the same branching criteria using the data from Facility B.
    Could you please tell me how to operate such a study?
    Please le...

    RyoM RyoM
    Discussions |
    Oct 3, 2023 12:59 AM
    1460 views | 2 replies
  • inverse prediction

    Dear, I saved a prediction formula of a linear weighted regression and would like to use it to make inverse predictions for a new y column.How may I do it? Best REgards, PY

    PYS PYS
    Discussions |
    Oct 2, 2023 9:12 AM
    1983 views | 3 replies

Latest Discussions

  • Want to run the same tuning design table for multiple y-variables

    I'm running bootstrap forest as a predicative model. I have hyperparameters I like but want to run multiple times (ex. 500 replicates) to find the random forest that gives me the best validation r square. I have the tuning design table built, but every time it runs for one predicted y-variable (there are 11 in my dataset) I have to manually choose the same design table every time. It's time consum...

    ClassCanary405 ClassCanary405
    Discussions |
    Oct 16, 2023 2:37 AM
    1165 views | 2 replies
  • Adding new data using previously develop random forest model

    Community,I am working with my colleague Kim on a project she used random forest to develop a prediction model for plant disease in potato based on soil properties. Here are our questions: How do we use new data with the already generated model that was already validated?How can we validate that the old predictive model is explaining the response variable?The predictive model indicates that with h...

    anaheilman anaheilman
    Discussions |
    Oct 13, 2023 11:30 AM
    1300 views | 1 replies
  • How to screen easily the non significant of many factors(~200 columns) before to perform a mulitple regression.

    I have many factor (~200 columns) and one response,i have many measures.Most of this factors show colinearity between them,is there a simple way to perform a first filter of the not relevant factors?Then in the remaining i will perform a multiple regression.

    Perpignan_italy Perpignan_italy
    Discussions |
    Oct 10, 2023 5:50 AM
    2084 views | 3 replies
  • SIMCA classification method: what alternative options do I have in JMP and what are the pros/cons?

    Hello, I am after a combination of guidance and education. I have recently come across SIMCA as a classification approach. I believe this is not something JMP can address at the moment so my question is, which alternative options can I explore to achieve a similar goal and what would be the advantages/disadvantages when compared to the SIMCA method?  I am currently using JMP 17 Thank you very much...

    CamillaLiscio CamillaLiscio
    Discussions |
    Oct 2, 2023 5:55 AM
    1342 views | 0 replies
  • How to transform and model non-normal dataset

    Hello, I'm working with a dataset produced from a 5-variable full factorial screening with 3 center points. The raw data is heavily skewed with an exponential distribution. I've tried log, log10, square root and various box-cox transformations and can't seem to get anything even nearly approaching a normal distribution.  ConditionPatterndata11+−−+−0.592−+−−−1.63−−−+−1.784+−++−0.455+−−−−1.376−++−−0...

    sanchez_dan sanchez_dan
    Discussions |
    Sep 26, 2023 1:36 PM
    1401 views | 1 replies

Latest Discussions

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