<?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: Why default setting model is scored best in SAS Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Data-Science/Why-default-setting-model-is-scored-best/m-p/839515#M10339</link>
    <description>&lt;P&gt;As mentioned, we need more details to help answer this question.&amp;nbsp; As a best practice, I want to point you to a paper that hits on several data mining topics.&amp;nbsp; It is several years old, but it is a fantastic paper to help in optimizing your data mining analysis.&amp;nbsp; It is called&amp;nbsp;Identifying and Overcoming Common Data Mining Mistakes.&amp;nbsp; It is found at the following URL:&lt;BR /&gt;&lt;BR /&gt;&amp;nbsp; &amp;nbsp;&lt;A href="https://support.sas.com/resources/papers/proceedings/proceedings/forum2007/073-2007.pdf" target="_blank"&gt;https://support.sas.com/resources/papers/proceedings/proceedings/forum2007/073-2007.pdf&lt;/A&gt;&lt;/P&gt;</description>
    <pubDate>Wed, 19 Oct 2022 20:51:27 GMT</pubDate>
    <dc:creator>CraigDeVault</dc:creator>
    <dc:date>2022-10-19T20:51:27Z</dc:date>
    <item>
      <title>Why default setting model is scored best</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Why-default-setting-model-is-scored-best/m-p/837964#M10332</link>
      <description>&lt;P&gt;I tried using a variable clustering node and a variable selection node to reduce the redundant variables, however, noticed that in the model comparison node, the random model scored best. why?&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 11 Oct 2022 23:51:02 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Why-default-setting-model-is-scored-best/m-p/837964#M10332</guid>
      <dc:creator>LMAlong999</dc:creator>
      <dc:date>2022-10-11T23:51:02Z</dc:date>
    </item>
    <item>
      <title>Re: Why default setting model is scored best</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Why-default-setting-model-is-scored-best/m-p/837969#M10333</link>
      <description>&lt;P&gt;Insufficient detail.&lt;/P&gt;
&lt;P&gt;Define the criteria used to determine best, share the data and show the code used (or generated by nodes) to make the models.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Then someone may be able to answer.&lt;/P&gt;</description>
      <pubDate>Wed, 12 Oct 2022 01:51:43 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Why-default-setting-model-is-scored-best/m-p/837969#M10333</guid>
      <dc:creator>ballardw</dc:creator>
      <dc:date>2022-10-12T01:51:43Z</dc:date>
    </item>
    <item>
      <title>Re: Why default setting model is scored best</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Why-default-setting-model-is-scored-best/m-p/839515#M10339</link>
      <description>&lt;P&gt;As mentioned, we need more details to help answer this question.&amp;nbsp; As a best practice, I want to point you to a paper that hits on several data mining topics.&amp;nbsp; It is several years old, but it is a fantastic paper to help in optimizing your data mining analysis.&amp;nbsp; It is called&amp;nbsp;Identifying and Overcoming Common Data Mining Mistakes.&amp;nbsp; It is found at the following URL:&lt;BR /&gt;&lt;BR /&gt;&amp;nbsp; &amp;nbsp;&lt;A href="https://support.sas.com/resources/papers/proceedings/proceedings/forum2007/073-2007.pdf" target="_blank"&gt;https://support.sas.com/resources/papers/proceedings/proceedings/forum2007/073-2007.pdf&lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Wed, 19 Oct 2022 20:51:27 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Why-default-setting-model-is-scored-best/m-p/839515#M10339</guid>
      <dc:creator>CraigDeVault</dc:creator>
      <dc:date>2022-10-19T20:51:27Z</dc:date>
    </item>
  </channel>
</rss>

