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    <title>topic Proc Logistic Oversampling in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Logistic-Oversampling/m-p/325002#M17160</link>
    <description>&lt;P&gt;I have a data set where the %age of bads are quite low.Can any one suggest a way to balance such a data set using SAS so that the logistic regression run gives a better result? Below is a sample. Thanks in advance!!&lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;ID  X1  X2  X3  X4  X5  Target
 1  87  400 2   0   0   0
 2  70  620 1   0   0   0
 3  66  410 3   0   0   0
 4  85  300 1   0   0   0
 5  100 200 4   0   0   0
 6  201 110 1   0   0   0
 7  132 513 3   0   0   0
 8  98  417 4   0   0   0
 9  397 620 1   0   0   1
10  98  700 5   0   0   1&lt;/CODE&gt;&lt;/PRE&gt;</description>
    <pubDate>Mon, 16 Jan 2017 10:47:15 GMT</pubDate>
    <dc:creator>Lopa2016</dc:creator>
    <dc:date>2017-01-16T10:47:15Z</dc:date>
    <item>
      <title>Proc Logistic Oversampling</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Logistic-Oversampling/m-p/325002#M17160</link>
      <description>&lt;P&gt;I have a data set where the %age of bads are quite low.Can any one suggest a way to balance such a data set using SAS so that the logistic regression run gives a better result? Below is a sample. Thanks in advance!!&lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;ID  X1  X2  X3  X4  X5  Target
 1  87  400 2   0   0   0
 2  70  620 1   0   0   0
 3  66  410 3   0   0   0
 4  85  300 1   0   0   0
 5  100 200 4   0   0   0
 6  201 110 1   0   0   0
 7  132 513 3   0   0   0
 8  98  417 4   0   0   0
 9  397 620 1   0   0   1
10  98  700 5   0   0   1&lt;/CODE&gt;&lt;/PRE&gt;</description>
      <pubDate>Mon, 16 Jan 2017 10:47:15 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Logistic-Oversampling/m-p/325002#M17160</guid>
      <dc:creator>Lopa2016</dc:creator>
      <dc:date>2017-01-16T10:47:15Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Logistic Oversampling</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Logistic-Oversampling/m-p/325006#M17161</link>
      <description>&lt;P&gt;Assign a Bayesian prior. See the prior statement.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 16 Jan 2017 11:17:58 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Logistic-Oversampling/m-p/325006#M17161</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2017-01-16T11:17:58Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Logistic Oversampling</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Logistic-Oversampling/m-p/325010#M17162</link>
      <description>&lt;P&gt;Thanks for your suggestion but can you help me with a code?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 16 Jan 2017 11:38:49 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Logistic-Oversampling/m-p/325010#M17162</guid>
      <dc:creator>Lopa2016</dc:creator>
      <dc:date>2017-01-16T11:38:49Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Logistic Oversampling</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Logistic-Oversampling/m-p/325134#M17172</link>
      <description>&lt;P&gt;No, but google can &lt;span class="lia-unicode-emoji" title=":slightly_smiling_face:"&gt;🙂&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="http://support.sas.com/kb/22/601.html" target="_blank"&gt;http://support.sas.com/kb/22/601.html&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 16 Jan 2017 21:28:57 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Logistic-Oversampling/m-p/325134#M17172</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2017-01-16T21:28:57Z</dc:date>
    </item>
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