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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).
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Learning Resources

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

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Latest Discussions

  • SHAP Analyses and SHAP Graph Builder

    Hi All,I have searched in the JMP community about SHAP Values and I am wondering if someone can direct me to some resources in how to evaluate SHAP values using JMP Pro 17. I understand how to populate the SHAP values (from the prediction profiler), but creating the graphs are a bit confusing at the point. I used the graph builder to build the graph, but I am wondering if there are videos or guide...

    NishaKumar2023 NishaKumar2023
    Discussions |
    Sep 13, 2024 7:29 AM
    4607 views | 7 replies

  • 关于JMP聚类使用过程出现的两个疑问

    我正在使用JMPpro进行一项样本量约10000份、包含20个变量的无监督机器学习聚类分析。在使用过程中出现了一些疑问，特此前来请教其他使用者或工程师，感谢你们能够抽出宝贵的时间阅读并耐心分析解答我的问题！ 疑问一：我已认真阅读该软件聚类分析功能介绍，JMP中的层次聚类适用于小样本的任意数据类型。那么，若数据中的20个变量分别属于混合型数据（包含连续型变量、离散型变量、有序型变量、名义型变量），请问我在进行层次聚类时是否需要事先把连续型变量和离散型变量进行标准化处理，随后在【标准化依据】选择“未标准化”呢？还是选择“未标准化”后软件会自动识别连续型变量和离散型变量并进行标准化处理，且有序型变量和名义型变量保持原始值呢（即无需在层次聚类前事先手动标准化处理）？ 疑问二：聚类分析属于机器学习中的无监督学习，若将19个变量进行层次聚类时，并在【依据】设置了某个（1个）二元名义型变量。那么，此次分...

    pnogau pnogau
    Discussions |
    Sep 10, 2024 4:45 AM
    2841 views | 4 replies

  • Bootstrap Forest Platform

    I am trying to use Bootstrap Forest with JMP17Pro. At the JMP support page I read that "The Bootstrap Forest red triangle menu contains the following options:" listing ROC Curve, Decision Threshold, Plot Actual by Predicted, among others. However, in my JMP pro there options do not show up, only a few of them. When clicking on the red triangle, most of these options are absent. I have checked the ...

    MargaridaSoares MargaridaSoares
    Discussions |
    Sep 10, 2024 1:30 AM
    1212 views | 2 replies

  • Multinomial Logistic Regression Confidence for Specific Parameter Changes

    Hi,  I have a multinomial logistic regression of 3 classes: 0, 1, and 2 and have associated individual models (via Fit Y by X) for N parameters. I am now looking into a sensitivity like study in which each parameter is assumed at certain levels (e.g. at min, max etc..). I have probabilities computed at each such parameter level. I like to rank order probability change in each class (0, 1 and 2) du...

    altug_bayram altug_bayram
    Discussions |
    Sep 5, 2024 9:02 AM
    805 views | 0 replies

  • Partial Least Squares - Baltic example

    Dear from JMP, About the Baltic PLS example (https://www.jmp.com/support/help/en/18.0/index.shtml#page/jmp/example-of-partial-least-squares.shtml#). I am trying to "RUN" the script to calculate the new observation, but I don´t no how to do. I already try to follow this guide (https://support.sas.com/documentation/onlinedoc/stat/131/pls.pdf) and doesn't work. So, my question is, after "run" the scr...

    lc_zenith lc_zenith
    Discussions |
    Sep 5, 2024 1:25 AM
    1123 views | 2 replies

Latest Discussions

  • Multinomial Logistic Regression Confidence for Specific Parameter Changes

    Hi,  I have a multinomial logistic regression of 3 classes: 0, 1, and 2 and have associated individual models (via Fit Y by X) for N parameters. I am now looking into a sensitivity like study in which each parameter is assumed at certain levels (e.g. at min, max etc..). I have probabilities computed at each such parameter level. I like to rank order probability change in each class (0, 1 and 2) du...

    altug_bayram altug_bayram
    Discussions |
    Sep 5, 2024 9:02 AM
    805 views | 0 replies

  • Partial Least Squares - Baltic example

    Dear from JMP, About the Baltic PLS example (https://www.jmp.com/support/help/en/18.0/index.shtml#page/jmp/example-of-partial-least-squares.shtml#). I am trying to "RUN" the script to calculate the new observation, but I don´t no how to do. I already try to follow this guide (https://support.sas.com/documentation/onlinedoc/stat/131/pls.pdf) and doesn't work. So, my question is, after "run" the scr...

    lc_zenith lc_zenith
    Discussions |
    Sep 5, 2024 1:25 AM
    1123 views | 2 replies

  • Building and validating zero-inflated negative binomial regression models

    Dear JMP community,I am presented with a problem of building a model using over-dispersed zero-inflated count data. I hope you can help me with this.I have attached both training and validation datasets to this post. My objective is to build my model on the training dataset and validate it using the validation dataset. I have not worked with such count data before and therefore do not know validat...

    stat_ranger stat_ranger
    Discussions |
    Sep 4, 2024 1:57 AM
    1037 views | 0 replies

  • Training and Validation R2s in Lasso/Elastic net

    Dear all, I use k-fold cross-validation in combination with penalized regression models (lasso, elastic net) and want to examine the (averaged) R2 values of the training/validation sets to check for overfitting and explained variance. I already searched around with the many options, but I can not find that. Is there a way to show this? It would be great, if that could be shown in the overview tabl...

    MarkusJH MarkusJH
    Discussions |
    Aug 23, 2024 10:52 AM
    3085 views | 5 replies

  • Database to practice experimental designs.

    Please, could you tell me where I can find a database to practice the different experimental designs, other than books? I would like scientific papers, but these only provide summary results. Thank you very much.

    CrhistianDoE CrhistianDoE
    Discussions |
    Aug 3, 2024 12:03 PM
    856 views | 1 replies

Latest Discussions

  • Multinomial Logistic Regression Confidence for Specific Parameter Changes

    Hi,  I have a multinomial logistic regression of 3 classes: 0, 1, and 2 and have associated individual models (via Fit Y by X) for N parameters. I am now looking into a sensitivity like study in which each parameter is assumed at certain levels (e.g. at min, max etc..). I have probabilities computed at each such parameter level. I like to rank order probability change in each class (0, 1 and 2) du...

    altug_bayram altug_bayram
    Discussions |
    Sep 5, 2024 9:02 AM
    805 views | 0 replies

  • Building and validating zero-inflated negative binomial regression models

    Dear JMP community,I am presented with a problem of building a model using over-dispersed zero-inflated count data. I hope you can help me with this.I have attached both training and validation datasets to this post. My objective is to build my model on the training dataset and validate it using the validation dataset. I have not worked with such count data before and therefore do not know validat...

    stat_ranger stat_ranger
    Discussions |
    Sep 4, 2024 1:57 AM
    1037 views | 0 replies

  • 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 ...

    Grizzly Grizzly
    Discussions |
    Jul 2, 2024 5:42 AM
    645 views | 0 replies

  • hybrid models

    Why doesn't a large and powerful program like JMPPRO contain hybrid models in time series such as the ARIMA-ANN model, ARMAX model, and others?

    Raaed Raaed
    Discussions |
    May 31, 2024 9:43 AM
    783 views | 0 replies

  • JMP Broadcasting statistical analysis

    We want to investigate the way which is suitable for searching predict and forecasting of medical region.
    For example, using stepwise parameter analysis, partial results of marketing will be used by data driven.
    Moreover we want to develop marketing extensive predictive analysis from marketing perspective.

    JMPLOVE1234 JMPLOVE1234
    Discussions |
    Apr 15, 2024 1:49 AM
    721 views | 0 replies
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Revolutionizing Spectral Baseline Correction in JMP: Harness the Power of Python Integration

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