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    <title>topic Re: how to test the logisctic model in SAS Forecasting and Econometrics</title>
    <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/how-to-test-the-logisctic-model/m-p/24124#M90</link>
    <description>I guess you are talking about classifying new observations. In &lt;B&gt;proc logistic&lt;/B&gt;, use the &lt;B&gt;outmodel&lt;/B&gt; option. This saves the fitted model information in a data set. For example,&lt;BR /&gt;
&lt;BR /&gt;
proc logistic data=training_data outmodel=mylib.Fitted_Model;&lt;BR /&gt;
....&lt;BR /&gt;
....&lt;BR /&gt;
&lt;BR /&gt;
Use the above data &lt;B&gt;Fitted_Model&lt;/B&gt; to model your new dataset,&lt;BR /&gt;
&lt;BR /&gt;
proc logistic noprint inmodel=mylib.Fitted_Model;&lt;BR /&gt;
      score data=New_Data out=Scored_Data;&lt;BR /&gt;
....&lt;BR /&gt;
&lt;BR /&gt;
&lt;B&gt;Scored_Data&lt;/B&gt; will have the data and the predicted values. &lt;BR /&gt;
&lt;BR /&gt;
Romakanta</description>
    <pubDate>Wed, 11 Jun 2008 11:37:22 GMT</pubDate>
    <dc:creator>datalligence</dc:creator>
    <dc:date>2008-06-11T11:37:22Z</dc:date>
    <item>
      <title>how to test the logisctic model</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/how-to-test-the-logisctic-model/m-p/24123#M89</link>
      <description>I am a new SAS user from Viet Nam, I try the logistic regression, I have built the model &amp;amp; I want to test the accuracy of this model by using other data set, but I don't how to do it.</description>
      <pubDate>Tue, 10 Jun 2008 03:38:52 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/how-to-test-the-logisctic-model/m-p/24123#M89</guid>
      <dc:creator>deleted_user</dc:creator>
      <dc:date>2008-06-10T03:38:52Z</dc:date>
    </item>
    <item>
      <title>Re: how to test the logisctic model</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/how-to-test-the-logisctic-model/m-p/24124#M90</link>
      <description>I guess you are talking about classifying new observations. In &lt;B&gt;proc logistic&lt;/B&gt;, use the &lt;B&gt;outmodel&lt;/B&gt; option. This saves the fitted model information in a data set. For example,&lt;BR /&gt;
&lt;BR /&gt;
proc logistic data=training_data outmodel=mylib.Fitted_Model;&lt;BR /&gt;
....&lt;BR /&gt;
....&lt;BR /&gt;
&lt;BR /&gt;
Use the above data &lt;B&gt;Fitted_Model&lt;/B&gt; to model your new dataset,&lt;BR /&gt;
&lt;BR /&gt;
proc logistic noprint inmodel=mylib.Fitted_Model;&lt;BR /&gt;
      score data=New_Data out=Scored_Data;&lt;BR /&gt;
....&lt;BR /&gt;
&lt;BR /&gt;
&lt;B&gt;Scored_Data&lt;/B&gt; will have the data and the predicted values. &lt;BR /&gt;
&lt;BR /&gt;
Romakanta</description>
      <pubDate>Wed, 11 Jun 2008 11:37:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/how-to-test-the-logisctic-model/m-p/24124#M90</guid>
      <dc:creator>datalligence</dc:creator>
      <dc:date>2008-06-11T11:37:22Z</dc:date>
    </item>
    <item>
      <title>Re: how to test the logisctic model</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/how-to-test-the-logisctic-model/m-p/24125#M91</link>
      <description>You can use Lift charts.&lt;BR /&gt;
&lt;BR /&gt;
 Lift charts are visual aids for measuring model performance. They consist of a lift curve and a baseline. The greater the area between the lift curve and the baseline, the better the model. &lt;BR /&gt;
&lt;BR /&gt;
----&lt;BR /&gt;
Calculate the model score in the other data set. Sort it by score and make 10 deciles.. Find out the sum of response and make the lift chart..&lt;BR /&gt;
&lt;BR /&gt;
Regards&lt;BR /&gt;
Vinux aka Richie</description>
      <pubDate>Fri, 20 Jun 2008 08:47:02 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/how-to-test-the-logisctic-model/m-p/24125#M91</guid>
      <dc:creator>deleted_user</dc:creator>
      <dc:date>2008-06-20T08:47:02Z</dc:date>
    </item>
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