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    <title>topic Re: Using XGBoost Model to Predict on a hold-out test set in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/401190#M65219</link>
    <description>&lt;P&gt;Hi Russ,&lt;/P&gt;&lt;P&gt;&amp;nbsp; I have not heard back from you regarding the previous message. PLease let me know whether you are amenable to a short phone call or not.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;thanks,&lt;/P&gt;&lt;P&gt;sukrit&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Thu, 15 Jul 2021 12:46:49 GMT</pubDate>
    <dc:creator>sukrit2020</dc:creator>
    <dc:date>2021-07-15T12:46:49Z</dc:date>
    <item>
      <title>Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/398526#M64953</link>
      <description>&lt;P&gt;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'.&amp;nbsp; Now, I have a separate hold-out test set on which I want to run the formulae to get the prediction.&amp;nbsp; 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. This also hinders me to run the model for the hold-out test set.&lt;/P&gt;</description>
      <pubDate>Fri, 09 Jun 2023 00:36:04 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/398526#M64953</guid>
      <dc:creator>sukrit2020</dc:creator>
      <dc:date>2023-06-09T00:36:04Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/398642#M64961</link>
      <description>&lt;P&gt;I'm not sure I know the answer to your question, but it appears you do not have any variables in your model (the column names are &lt;EM&gt;validation&lt;/EM&gt; and &lt;I&gt;training and shrinkage&amp;nbsp;predator validation&lt;/I&gt;)? &amp;nbsp;So the formula is a function of those column names. Either re-write the model in terms of variables or re-name the columns of your hold out data set?&lt;/P&gt;</description>
      <pubDate>Tue, 06 Jul 2021 15:59:33 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/398642#M64961</guid>
      <dc:creator>statman</dc:creator>
      <dc:date>2021-07-06T15:59:33Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/398762#M64964</link>
      <description>&lt;P&gt;I added the jmp file. If you look into the XGBoost model, you can see the details. I have 17 variables.&lt;/P&gt;</description>
      <pubDate>Tue, 06 Jul 2021 17:20:41 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/398762#M64964</guid>
      <dc:creator>sukrit2020</dc:creator>
      <dc:date>2021-07-06T17:20:41Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/398971#M64973</link>
      <description>&lt;P&gt;Your data set is the same as the one used in the help menu for the XGBoost add-in. &amp;nbsp;Did you follow the steps shown in the application of the platform?&lt;/P&gt;</description>
      <pubDate>Tue, 06 Jul 2021 19:55:00 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/398971#M64973</guid>
      <dc:creator>statman</dc:creator>
      <dc:date>2021-07-06T19:55:00Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399041#M64985</link>
      <description>&lt;P&gt;Yes. I did. I was not able to still get the formulae.&lt;/P&gt;</description>
      <pubDate>Tue, 06 Jul 2021 22:54:21 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399041#M64985</guid>
      <dc:creator>sukrit2020</dc:creator>
      <dc:date>2021-07-06T22:54:21Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399408#M65027</link>
      <description>&lt;P&gt;Sorry I haven't had time to look at your data. &amp;nbsp;I'm also not very experienced with the platform, but my guess is you should use the platform to find the significant factors and then re-write your model in fit model and run it and save the prediction formula...but again, I'm not experienced here. &amp;nbsp;Perhaps there is an easier way to get the actual model in terms of the variables in the data table...&lt;/P&gt;</description>
      <pubDate>Wed, 07 Jul 2021 19:22:42 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399408#M65027</guid>
      <dc:creator>statman</dc:creator>
      <dc:date>2021-07-07T19:22:42Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399599#M65056</link>
      <description>&lt;P&gt;Can you show me over a webex call?&lt;/P&gt;</description>
      <pubDate>Thu, 08 Jul 2021 14:47:54 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399599#M65056</guid>
      <dc:creator>sukrit2020</dc:creator>
      <dc:date>2021-07-08T14:47:54Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399611#M65058</link>
      <description>&lt;P&gt;I suggest getting in touch with Russ:&amp;nbsp;&lt;LI-MESSAGE title="XGBoost Add-In for JMP Pro" uid="319383" url="https://community.jmp.com/t5/JMP-Add-Ins/XGBoost-Add-In-for-JMP-Pro/m-p/319383#U319383" discussion_style_icon_css="lia-mention-container-editor-message lia-img-icon-tkb-thread lia-fa-icon lia-fa-tkb lia-fa-thread lia-fa"&gt;&lt;/LI-MESSAGE&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 09 Jul 2021 11:13:23 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399611#M65058</guid>
      <dc:creator>statman</dc:creator>
      <dc:date>2021-07-09T11:13:23Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399785#M65081</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.jmp.com/t5/user/viewprofilepage/user-id/18306"&gt;@sukrit2020&lt;/a&gt;&amp;nbsp;,&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;A recommended approach is to append your separate hold-out test set to the main data as new rows with the Y target values set to missing. Then the formula will automatically create predictions on those rows.&amp;nbsp; &amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Also, it's important to note that XGBoost handles validation differently than other JMP platforms.&amp;nbsp; &amp;nbsp;If the validation column is Nominal, it will automatically do full k-fold with each of the levels.&amp;nbsp; &amp;nbsp;This is why the formula looks like it does.&amp;nbsp; &amp;nbsp;This can be confusing if your validation column has two levels, e.g. "Validation" and "Training".&amp;nbsp; &amp;nbsp;In this case XGBoost would actually do 2-fold, holding out each subset regardless of their values.&amp;nbsp;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;A better way to set up your folds is to use the Make K-Fold Columns utility, and then use those as your Validation columns.&amp;nbsp; I feel repeated k-fold is a much better way to validate your model than using a single holdout set.&amp;nbsp; &amp;nbsp;If you really want to only do a single holdout, you must set the type of the Validation column to Continuous, with value 0 corresponding to training and 1 to validation.&lt;/P&gt;</description>
      <pubDate>Fri, 09 Jul 2021 11:43:21 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/399785#M65081</guid>
      <dc:creator>russ_wolfinger</dc:creator>
      <dc:date>2021-07-09T11:43:21Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/400005#M65115</link>
      <description>&lt;P&gt;Hi Russ,&lt;/P&gt;&lt;P&gt;&amp;nbsp; Can we set up a webex where you can show me the procedure? I am little new to JMP and thus could not fully follow your instructions.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;thanks,&lt;/P&gt;&lt;P&gt;sukrit&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 10 Jul 2021 16:33:12 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/400005#M65115</guid>
      <dc:creator>sukrit2020</dc:creator>
      <dc:date>2021-07-10T16:33:12Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/401190#M65219</link>
      <description>&lt;P&gt;Hi Russ,&lt;/P&gt;&lt;P&gt;&amp;nbsp; I have not heard back from you regarding the previous message. PLease let me know whether you are amenable to a short phone call or not.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;thanks,&lt;/P&gt;&lt;P&gt;sukrit&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Thu, 15 Jul 2021 12:46:49 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/401190#M65219</guid>
      <dc:creator>sukrit2020</dc:creator>
      <dc:date>2021-07-15T12:46:49Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/403362#M65395</link>
      <description>&lt;P&gt;OK&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="2021-07-23_1729.png" style="width: 353px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/34474i87ADAD6D3A01FB18/image-size/large?v=v2&amp;amp;px=999" role="button" title="2021-07-23_1729.png" alt="2021-07-23_1729.png" /&gt;&lt;/span&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 23 Jul 2021 09:44:53 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/403362#M65395</guid>
      <dc:creator>lwx228</dc:creator>
      <dc:date>2021-07-23T09:44:53Z</dc:date>
    </item>
    <item>
      <title>Re: Using XGBoost Model to Predict on a hold-out test set</title>
      <link>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/404461#M65493</link>
      <description>&lt;P&gt;Can you show me how you got this? I could not get this.&lt;/P&gt;</description>
      <pubDate>Tue, 27 Jul 2021 20:51:33 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Using-XGBoost-Model-to-Predict-on-a-hold-out-test-set/m-p/404461#M65493</guid>
      <dc:creator>sukrit2020</dc:creator>
      <dc:date>2021-07-27T20:51:33Z</dc:date>
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