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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

  • JMP Crashing

    I wrote a script where if a folder does not exist, then a folder will be created. The path is to a shared network folder. I have modify access to the shared folder and the script works fine for me. However, when a colleague who has only read access to the shared folder, runs the script JMP crashes when it get to the below section of code. JMP just completely closes everything, even the log file so...

    B1234 B1234
    Discussions |
    Aug 13, 2021 2:31 AM
    2628 views | 2 replies
  • kNN (k Nearest Neighbors) Displays Different Fit Statistics in JMP Pro v16

    A heads-up to those of you hoping to use kNN in JMP v16 with cross-validation... The Word attachment indicates that, for k = 3: Training R2Validation R22nd exhibit0.928390.908743rd exhibit0.97060.9086 The validation R2s are close, but not identical. Although this is minor, the difference in the training R2s is not: 0.93 vs 0.97. Documentation about this issue is not available, although there is me...

    MAS MAS
    Discussions |
    Aug 11, 2021 4:02 PM
    2037 views | 1 replies
  • Using XGBoost Model to Predict on a hold-out test set

    I am using JMP 16. I installed the XGBoost addin. I developed a xgbbost model using this. I saved the model in the data table using 'Save Prediction formulae'.  Now, I have a separate hold-out test set on which I want to run the formulae to get the prediction.  If I click the formulae (see attached figure), I found that the formulae depend on the training and validation set, which seems odd to me....

    sukrit2020 sukrit2020
    Discussions |
    Jul 27, 2021 1:51 PM
    8379 views | 12 replies
  • Best model in multinomial logistics regression model

    Hello What models use to select variables in a multinomial logistics regression model to have the best AIC ? and select the best variables ?
    I tried with the regression step by step but I don't understand that doesn't work, I have a less good confusion matrix than with my model of nominal logistic regression with all my variablesThank you

    Emma1 Emma1
    Discussions |
    Jul 21, 2021 1:35 PM
    1470 views | 2 replies
  • Confusion matrix "training"

    Hello, I have no question about the confusion matrix of a multinomial logistic regression model Here's there is the variable Y with 3 modalities: 1,2,3   Does "Training" mean that JMP automatically does a learning database to learn the model?Indeed when I calculate the total number of observations on my confusion matrix : 311+79+37+98+209+59+48+57+187 = 1085While my database is 1369 rowsAnd 1085/1...

    Emma1 Emma1
    Discussions |
    Jul 21, 2021 10:34 AM
    1732 views | 1 replies

Latest Discussions

  • kNN (k Nearest Neighbors) Displays Different Fit Statistics in JMP Pro v16

    A heads-up to those of you hoping to use kNN in JMP v16 with cross-validation... The Word attachment indicates that, for k = 3: Training R2Validation R22nd exhibit0.928390.908743rd exhibit0.97060.9086 The validation R2s are close, but not identical. Although this is minor, the difference in the training R2s is not: 0.93 vs 0.97. Documentation about this issue is not available, although there is me...

    MAS MAS
    Discussions |
    Aug 11, 2021 4:02 PM
    2037 views | 1 replies
  • Using XGBoost Model to Predict on a hold-out test set

    I am using JMP 16. I installed the XGBoost addin. I developed a xgbbost model using this. I saved the model in the data table using 'Save Prediction formulae'.  Now, I have a separate hold-out test set on which I want to run the formulae to get the prediction.  If I click the formulae (see attached figure), I found that the formulae depend on the training and validation set, which seems odd to me....

    sukrit2020 sukrit2020
    Discussions |
    Jul 27, 2021 1:51 PM
    8379 views | 12 replies
  • Best model in multinomial logistics regression model

    Hello What models use to select variables in a multinomial logistics regression model to have the best AIC ? and select the best variables ?
    I tried with the regression step by step but I don't understand that doesn't work, I have a less good confusion matrix than with my model of nominal logistic regression with all my variablesThank you

    Emma1 Emma1
    Discussions |
    Jul 21, 2021 1:35 PM
    1470 views | 2 replies
  • Confusion matrix "training"

    Hello, I have no question about the confusion matrix of a multinomial logistic regression model Here's there is the variable Y with 3 modalities: 1,2,3   Does "Training" mean that JMP automatically does a learning database to learn the model?Indeed when I calculate the total number of observations on my confusion matrix : 311+79+37+98+209+59+48+57+187 = 1085While my database is 1369 rowsAnd 1085/1...

    Emma1 Emma1
    Discussions |
    Jul 21, 2021 10:34 AM
    1732 views | 1 replies
  • Predictor screening

    For predictor screening in JMP bootstrap forest is used; this works very well however why is this method chosen and not boosted tree which is also a very powerful method? Does JMP use XGboosted?

    frankderuyck frankderuyck
    Discussions |
    Jul 6, 2021 10:30 AM
    3575 views | 4 replies

Latest Discussions

  • What does it mean when the solution path for Elastic Net is not single-valued?

    Dear JMP Community,   (W10, 64-bit, JMP Pro 15.2.1)   I am running a model to assess the active predictors. I am doing this by using the Autovalidation add-in to generate a Null Factor for my data. I then use the GenReg platform to find estimates for each possible X-factor and then Bootstrap those estimates to get a better assessment of the contributions to the response. I came across a very stran...

    SDF1 SDF1
    Discussions |
    Feb 15, 2021 12:35 PM
    1443 views | 0 replies
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