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    <title>topic Re: how to use Model comparison node in SAS Enterprise Miner on different Segments in SAS Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Data-Science/how-to-use-Model-comparison-node-in-SAS-Enterprise-Miner-on/m-p/262128#M3853</link>
    <description>Hi, 

What you can do is to build a segment variable, say, segment_model by consolidating your segmentation logic. For example, 

if Gender = "F" and income="low", then segment_model=1; else 
if Gender = "F" and income="mid", then segment_model=2; else 
if Gender = "F" and income="high", then segment_model=3;...

just build all the segmentation combinations into one variable. 

After reading the data set into EM, turn this new variable segment_model's role into Segment. Make sure there is only ONE variable acting as Segment Role. 

Then look into EM online example under START and END group. You should learn how to build models on this segment variable quickly. Then after END group you can connect Model Comparison Node. The Comparison node will report model statistics by the segments.

You can always run the model based on the whole sample alongside this START-END group process. Hope this help? Jason Xin</description>
    <pubDate>Thu, 07 Apr 2016 16:31:11 GMT</pubDate>
    <dc:creator>JasonXin</dc:creator>
    <dc:date>2016-04-07T16:31:11Z</dc:date>
    <item>
      <title>how to use Model comparison node in SAS Enterprise Miner on different Segments</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/how-to-use-Model-comparison-node-in-SAS-Enterprise-Miner-on/m-p/261889#M3848</link>
      <description>&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I am trying to build a model on an Interval target using SAS Enterprise Miner (v. 13.2) using Log transformation&amp;nbsp;of the target and using the Linear Regression.&lt;/P&gt;&lt;P&gt;I have segmented the population based on different characteristics (like Low/High-income customers as model 1&amp;amp;2 and Male/Female customers as model 3&amp;amp;4) and ran a model for each segment.&lt;/P&gt;&lt;P&gt;Now trying to come up with the best segmentation based on the model outputs, I would like to use model comparison node to compare the fit statistics. the problem is, I cannot find a way to merge the segments together (1&amp;amp;2) vs. (3&amp;amp;4) so that I can compare the performance of the models together (Gender vs. Income level).&lt;/P&gt;&lt;P&gt;I used the "Append" node to merge two segments&amp;nbsp;on each model but not successful.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I appreciate any help.&lt;/P&gt;&lt;P&gt;Sam&lt;/P&gt;</description>
      <pubDate>Wed, 06 Apr 2016 18:30:24 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/how-to-use-Model-comparison-node-in-SAS-Enterprise-Miner-on/m-p/261889#M3848</guid>
      <dc:creator>Sam_zirak</dc:creator>
      <dc:date>2016-04-06T18:30:24Z</dc:date>
    </item>
    <item>
      <title>Re: how to use Model comparison node in SAS Enterprise Miner on different Segments</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/how-to-use-Model-comparison-node-in-SAS-Enterprise-Miner-on/m-p/262001#M3849</link>
      <description>&lt;P&gt;Moved to the appropriate Data Mining forum.&lt;/P&gt;</description>
      <pubDate>Thu, 07 Apr 2016 07:03:32 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/how-to-use-Model-comparison-node-in-SAS-Enterprise-Miner-on/m-p/262001#M3849</guid>
      <dc:creator>LinusH</dc:creator>
      <dc:date>2016-04-07T07:03:32Z</dc:date>
    </item>
    <item>
      <title>Re: how to use Model comparison node in SAS Enterprise Miner on different Segments</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/how-to-use-Model-comparison-node-in-SAS-Enterprise-Miner-on/m-p/262128#M3853</link>
      <description>Hi, 

What you can do is to build a segment variable, say, segment_model by consolidating your segmentation logic. For example, 

if Gender = "F" and income="low", then segment_model=1; else 
if Gender = "F" and income="mid", then segment_model=2; else 
if Gender = "F" and income="high", then segment_model=3;...

just build all the segmentation combinations into one variable. 

After reading the data set into EM, turn this new variable segment_model's role into Segment. Make sure there is only ONE variable acting as Segment Role. 

Then look into EM online example under START and END group. You should learn how to build models on this segment variable quickly. Then after END group you can connect Model Comparison Node. The Comparison node will report model statistics by the segments.

You can always run the model based on the whole sample alongside this START-END group process. Hope this help? Jason Xin</description>
      <pubDate>Thu, 07 Apr 2016 16:31:11 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/how-to-use-Model-comparison-node-in-SAS-Enterprise-Miner-on/m-p/262128#M3853</guid>
      <dc:creator>JasonXin</dc:creator>
      <dc:date>2016-04-07T16:31:11Z</dc:date>
    </item>
    <item>
      <title>Re: how to use Model comparison node in SAS Enterprise Miner on different Segments</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/how-to-use-Model-comparison-node-in-SAS-Enterprise-Miner-on/m-p/262455#M3865</link>
      <description>&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;It works very well.&lt;/P&gt;&lt;P&gt;I cannot thank you enough for your guidance Jason.&lt;/P&gt;&lt;P&gt;Using start and eng groups is something I had never heard of before and it is incredibly powerful and time-saving. That is exactly what I was looking for and it will save me a huge amount of time on any project that I work on.&lt;/P&gt;&lt;P&gt;Thanks a million!&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Sam&lt;/P&gt;</description>
      <pubDate>Fri, 08 Apr 2016 14:44:59 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/how-to-use-Model-comparison-node-in-SAS-Enterprise-Miner-on/m-p/262455#M3865</guid>
      <dc:creator>Sam_zirak</dc:creator>
      <dc:date>2016-04-08T14:44:59Z</dc:date>
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