<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: Data Ponderation - Decision Tree in SAS Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Data-Science/Data-Ponderation-Decision-Tree/m-p/17772#M92</link>
    <description>Hi Wayne,&lt;BR /&gt;
I was looking the node you comment, but I can not find it. Another node that I think I'll try to use is the MBR. Where do I locate the decision node?&lt;BR /&gt;
&lt;BR /&gt;
thanks for you help&lt;BR /&gt;
Lucho</description>
    <pubDate>Fri, 07 May 2010 22:01:59 GMT</pubDate>
    <dc:creator>deleted_user</dc:creator>
    <dc:date>2010-05-07T22:01:59Z</dc:date>
    <item>
      <title>Data Ponderation - Decision Tree</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Data-Ponderation-Decision-Tree/m-p/17770#M90</link>
      <description>Hi,&lt;BR /&gt;
&lt;BR /&gt;
I'm doing a decision tree with n=2800 y 1=11% (0=89% of course) and I have a doubt:&lt;BR /&gt;
&lt;BR /&gt;
i want to know if i need a ponderation of my cases, because my target  is Yes=11%. wich node do i have to use?&lt;BR /&gt;
&lt;BR /&gt;
&lt;BR /&gt;
thanks for your help&lt;BR /&gt;
&lt;BR /&gt;
Lucho</description>
      <pubDate>Fri, 07 May 2010 16:32:17 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Data-Ponderation-Decision-Tree/m-p/17770#M90</guid>
      <dc:creator>deleted_user</dc:creator>
      <dc:date>2010-05-07T16:32:17Z</dc:date>
    </item>
    <item>
      <title>Re: Data Ponderation - Decision Tree</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Data-Ponderation-Decision-Tree/m-p/17771#M91</link>
      <description>Hi Lucho,  I am sorry if I am not addressing or understanding your question.  You have a target event rate of 11% which may include include enough cases to develop a good tree classification model without using weights/oversampling.  Use the Data Partition node which will automatically stratify by the binary target and given you have 2800 observations perhaps output only training and validation data.  Train the tree model and check for stability.&lt;BR /&gt;
&lt;BR /&gt;
 In case of a poor model with no or  just a few poor splits consider using the decison processing capability of EM (see the Decision node and also review the predictive modeling chapter - see topics rare events and decision processing which discusses using weights as well)   &lt;BR /&gt;
&lt;BR /&gt;
This paper may also be useful: &lt;A href="http://www2.sas.com/proceedings/forum2007/073-2007.pdf" target="_blank"&gt;http://www2.sas.com/proceedings/forum2007/073-2007.pdf&lt;/A&gt;</description>
      <pubDate>Fri, 07 May 2010 18:21:53 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Data-Ponderation-Decision-Tree/m-p/17771#M91</guid>
      <dc:creator>WayneThompson</dc:creator>
      <dc:date>2010-05-07T18:21:53Z</dc:date>
    </item>
    <item>
      <title>Re: Data Ponderation - Decision Tree</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Data-Ponderation-Decision-Tree/m-p/17772#M92</link>
      <description>Hi Wayne,&lt;BR /&gt;
I was looking the node you comment, but I can not find it. Another node that I think I'll try to use is the MBR. Where do I locate the decision node?&lt;BR /&gt;
&lt;BR /&gt;
thanks for you help&lt;BR /&gt;
Lucho</description>
      <pubDate>Fri, 07 May 2010 22:01:59 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Data-Ponderation-Decision-Tree/m-p/17772#M92</guid>
      <dc:creator>deleted_user</dc:creator>
      <dc:date>2010-05-07T22:01:59Z</dc:date>
    </item>
  </channel>
</rss>

