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    <title>topic Re: Accessing out of fold metrics for K-Fold CV in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932491#M108906</link>
    <description>&lt;P&gt;Hi Victor,&lt;/P&gt;
&lt;P&gt;Thanks for the response. As far as I can see, this only works with default settings for each method. I have configurations from tuning designs that I would like to compare using fold data. It doesn't look like this is possible unless I run each fold manually, which will be very time consuming. Am I missing something here?&lt;/P&gt;</description>
    <pubDate>Wed, 25 Feb 2026 08:51:07 GMT</pubDate>
    <dc:creator>CentroidError56</dc:creator>
    <dc:date>2026-02-25T08:51:07Z</dc:date>
    <item>
      <title>Accessing out of fold metrics for K-Fold CV</title>
      <link>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932392#M108887</link>
      <description>&lt;P&gt;Is there any way to access the out of fold metrics when using K-Fold CV with methods like Neural and SVM? As far as I know JMP only reports metrics from the best performing fold, which isn't very useful at all.&lt;/P&gt;</description>
      <pubDate>Tue, 24 Feb 2026 18:18:02 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932392#M108887</guid>
      <dc:creator>CentroidError56</dc:creator>
      <dc:date>2026-02-24T18:18:02Z</dc:date>
    </item>
    <item>
      <title>Re: Accessing out of fold metrics for K-Fold CV</title>
      <link>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932414#M108890</link>
      <description>&lt;P&gt;Hi &lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/47547"&gt;@CentroidError56&lt;/a&gt;,&lt;/P&gt;
&lt;P&gt;Yes, please use the platform &lt;A href="https://www.jmp.com/support/help/en/19.0/#page/jmp/model-screening.shtml#" target="_self"&gt;Model Screening&lt;/A&gt; with the models you want to test checked to get access to validation folds results in the report.&lt;/P&gt;
&lt;P&gt;&lt;A title="Training, Validation, and Test Measures of Fit" href="https://www.jmp.com/support/help/en/19.0/#page/jmp/training-validation-and-test-measures-of-fit.shtml" target="_self"&gt;Training, Validation, and Test Measures of Fit&lt;/A&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;From the Model Screening platform options, you can &lt;A href="http://Save%20KFold Results Table" target="_self"&gt;save a KFolds Results table&lt;/A&gt;.&lt;/P&gt;
&lt;P&gt;Hope this solution will help you,&lt;/P&gt;</description>
      <pubDate>Tue, 24 Feb 2026 19:15:22 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932414#M108890</guid>
      <dc:creator>Victor_G</dc:creator>
      <dc:date>2026-02-24T19:15:22Z</dc:date>
    </item>
    <item>
      <title>Re: Accessing out of fold metrics for K-Fold CV</title>
      <link>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932491#M108906</link>
      <description>&lt;P&gt;Hi Victor,&lt;/P&gt;
&lt;P&gt;Thanks for the response. As far as I can see, this only works with default settings for each method. I have configurations from tuning designs that I would like to compare using fold data. It doesn't look like this is possible unless I run each fold manually, which will be very time consuming. Am I missing something here?&lt;/P&gt;</description>
      <pubDate>Wed, 25 Feb 2026 08:51:07 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932491#M108906</guid>
      <dc:creator>CentroidError56</dc:creator>
      <dc:date>2026-02-25T08:51:07Z</dc:date>
    </item>
    <item>
      <title>Re: Accessing out of fold metrics for K-Fold CV</title>
      <link>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932498#M108908</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/47547"&gt;@CentroidError56&lt;/a&gt;,&lt;/P&gt;
&lt;P&gt;You're right, this option will only work with default hyperparameter settings.&amp;nbsp;&lt;BR /&gt;Here is how I would do with specific hyperparameter configurations to be tested on the same folds:&lt;/P&gt;
&lt;OL&gt;
&lt;LI&gt;Create a K-folds validation column using the&amp;nbsp;&lt;A href="https://www.jmp.com/support/help/en/19.0/#page/jmp/make-validation-column.shtml?_gl=1*1k28hoi*_up*MQ..*_ga*NDc2MDQ1NTkuMTc3MjAxMTE0MA..*_ga_BRNVBEC1RS*czE3NzIwMTExMzkkbzEkZzAkdDE3NzIwMTExMzkkajYwJGwwJGgw#" target="_blank" rel="noopener"&gt;Make Validation Column&lt;/A&gt;&amp;nbsp;platform. Specify the stratification columns (the X's) and the target (Y). You can then define the number of folds and set a random seed.&lt;BR /&gt;&lt;BR /&gt;&lt;/LI&gt;
&lt;LI&gt;Launch the modeling platform of your choice with this K-folds column in the validation role. &lt;BR /&gt;In this example for illustration, I used the JMP Diabetes dataset and the SVM platform. I realized a tuning design to find 3 appropriate hyperparameters settings (models 2, 3 and 20) :&lt;BR /&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Capture d'écran 2026-02-25 102200.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/94476i8762CD0414B43F8B/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Capture d'écran 2026-02-25 102200.png" alt="Capture d'écran 2026-02-25 102200.png" /&gt;&lt;/span&gt;&lt;/LI&gt;
&lt;LI&gt;
&lt;P&gt;I then press CTRL + click on the option &lt;A href="https://www.jmp.com/support/help/en/19.0/#page/jmp/support-vector-machines-platform-options.shtml?_gl=1*8h7vs*_up*MQ..*_ga*NDc2MDQ1NTkuMTc3MjAxMTE0MA..*_ga_BRNVBEC1RS*czE3NzIwMTExMzkkbzEkZzAkdDE3NzIwMTExMzkkajYwJGwwJGgw#" target="_self"&gt;Publish prediction formula&lt;/A&gt; (available in the red triangle next to any model). A new Formula Depot window is created with the formula of the three models seen earlier :&lt;/P&gt;
&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Capture d'écran 2026-02-25 102455.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/94477iF771C501BB402192/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Capture d'écran 2026-02-25 102455.png" alt="Capture d'écran 2026-02-25 102455.png" /&gt;&lt;/span&gt;&lt;/LI&gt;
&lt;LI&gt;
&lt;P&gt;In the red triangle next to Formula Depot, I click on the option &lt;A href="https://www.jmp.com/support/help/en/19.0/#page/jmp/model-comparison.shtml#ww74115" target="_blank" rel="noopener"&gt;Model Comparison&lt;/A&gt;&amp;nbsp;and select my three models :&lt;/P&gt;
&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Capture d'écran 2026-02-25 102708.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/94478i2094D8F7CF7666FE/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Capture d'écran 2026-02-25 102708.png" alt="Capture d'écran 2026-02-25 102708.png" /&gt;&lt;/span&gt;&lt;BR /&gt;
&lt;P&gt;JMP notices than my 5-folds validation column is used for all models, and ask if it can use it as a grouping column, so I click yes to have individual models results for each fold. &lt;/P&gt;
&lt;/LI&gt;
&lt;LI&gt;&amp;nbsp;I have now access to the individual folds measure of performances for each of the three models :&lt;BR /&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Capture d'écran 2026-02-25 102846.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/94479iA1FBEA198996B63A/image-size/medium?v=v2&amp;amp;px=400" role="button" title="Capture d'écran 2026-02-25 102846.png" alt="Capture d'écran 2026-02-25 102846.png" /&gt;&lt;/span&gt;&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;This method should work no matter the modeling platform used, as it is only using the models prediction formula, so you can combine different models types.&lt;/P&gt;
&lt;P&gt;Hope this answer will solve your problem,&lt;/P&gt;</description>
      <pubDate>Wed, 25 Feb 2026 09:33:29 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932498#M108908</guid>
      <dc:creator>Victor_G</dc:creator>
      <dc:date>2026-02-25T09:33:29Z</dc:date>
    </item>
    <item>
      <title>Re: Accessing out of fold metrics for K-Fold CV</title>
      <link>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932503#M108910</link>
      <description>&lt;P&gt;Hi Victor,&lt;/P&gt;
&lt;P&gt;This works! Thank you very much!&lt;/P&gt;</description>
      <pubDate>Wed, 25 Feb 2026 09:54:11 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Accessing-out-of-fold-metrics-for-K-Fold-CV/m-p/932503#M108910</guid>
      <dc:creator>CentroidError56</dc:creator>
      <dc:date>2026-02-25T09:54:11Z</dc:date>
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