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    <title>topic Scoring SAS Enterprise Miner in SAS Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Data-Science/Scoring-SAS-Enterprise-Miner/m-p/396232#M6031</link>
    <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am trying to score new data. I have a classification problem. One of the variables is the target. It is set to 1 if true and 0 if false. But how will i know from the score node output, how many have been classified into one class and another into another class? Isn't that the point of scoring?&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks&lt;/P&gt;&lt;P&gt;Dee&lt;/P&gt;</description>
    <pubDate>Fri, 15 Sep 2017 09:55:37 GMT</pubDate>
    <dc:creator>dee2017</dc:creator>
    <dc:date>2017-09-15T09:55:37Z</dc:date>
    <item>
      <title>Scoring SAS Enterprise Miner</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Scoring-SAS-Enterprise-Miner/m-p/396232#M6031</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am trying to score new data. I have a classification problem. One of the variables is the target. It is set to 1 if true and 0 if false. But how will i know from the score node output, how many have been classified into one class and another into another class? Isn't that the point of scoring?&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks&lt;/P&gt;&lt;P&gt;Dee&lt;/P&gt;</description>
      <pubDate>Fri, 15 Sep 2017 09:55:37 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Scoring-SAS-Enterprise-Miner/m-p/396232#M6031</guid>
      <dc:creator>dee2017</dc:creator>
      <dc:date>2017-09-15T09:55:37Z</dc:date>
    </item>
    <item>
      <title>Re: Scoring SAS Enterprise Miner</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Scoring-SAS-Enterprise-Miner/m-p/396392#M6034</link>
      <description>&lt;P&gt;&lt;SPAN&gt;For your analysis, SAS Enterprise Miner generated&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;P_PATIENT_ALIVE_FLAG1: the probability that PATIENT_ALIVE_FLAG = 1&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;P_PATIENT_ALIVE_FLAG0: the probability that PATIENT_ALIVE_FLAG = 0&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;The assignment to an outcome is ultimately a modeling decision. &amp;nbsp;In your previous note, you shared results which indicated that you had a target variable named&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;PATIENT_ALIVE_FLAG&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;which could be either 1 or 0 (alive or dead, presumably). &amp;nbsp; In this case, SAS Enterprise Miner would create two prediction variables to store the probability of each outcome:&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; P_PATIENT_ALIVE_FLAG1 = &amp;nbsp;the probability that PATIENT_ALIVE_FLAG=1 for the observation&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; P_PATIENT_ALIVE_FLAG0 = &amp;nbsp;the probability that PATIENT_ALIVE_FLAG=0 for the observation&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;as well as an 'Into' variable which predicts which class is most likely based on the larger of the two values above, and this variable would be named (in this example)&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; I_PATIENT_ALIVE_FLAG = the most likely outcome based on the two probabilities described above&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;It is possible, however, that you might not want to predict PATIENT_ALIVE_FLAG = 0 unless there is a very high probability that this was the case (e.g. perhaps only when P_PATIENT_ALIVE_FLAG0 is greater than 0.9). &amp;nbsp; In any case, the software can compute the probabilities but you need to decide what the threshold should be to determine if you predict PATIENT_ALIVE_FLAG=1 or PATIENT_ALIVE_FLAG=0. &amp;nbsp;It is then easy to assign the observations to a category based on the cutoff you choose. &amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;Hope this helps!&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;Doug&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 15 Sep 2017 15:26:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Scoring-SAS-Enterprise-Miner/m-p/396392#M6034</guid>
      <dc:creator>DougWielenga</dc:creator>
      <dc:date>2017-09-15T15:26:27Z</dc:date>
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