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    <title>topic Re: Classifying emails with SAS VTA and VDMML in SAS Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Data-Science/Classifying-emails-with-SAS-VTA-and-VDMML/m-p/930597#M10823</link>
    <description>&lt;P&gt;I'm not so sure this is the best little project to learn SAS programming ... but anyway.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;In SAS terminology&amp;nbsp;&lt;SPAN&gt;multi-class classification (and multi-label&amp;nbsp;classification) are always supervised.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;You probably need&amp;nbsp;unsupervised learning &lt;STRONG&gt;clustering&lt;/STRONG&gt; classifiers or &lt;STRONG&gt;topic detection&lt;/STRONG&gt; capabilities.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;If there's no pipeline template for clustering in Model Studio (VDMML), you can always build such a pipeline yourself starting from a data node (or an empty pipeline).&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;After you have used Singular Value Decomposition (SVD) or&amp;nbsp;&lt;/SPAN&gt;Latent Dirichlet allocation (LDA) to reduce the dimensionality of the weighted term-by-document frequency matrix, you can perfectly apply some clustering algorithms. But every e-mail will belong to only 1 cluster. If you use the topic detection in VTA, then a single e-mail may contain several topics.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Koen&lt;/P&gt;
&lt;P&gt;&lt;LI-WRAPPER&gt;&lt;/LI-WRAPPER&gt;&lt;/P&gt;</description>
    <pubDate>Mon, 03 Jun 2024 11:21:28 GMT</pubDate>
    <dc:creator>sbxkoenk</dc:creator>
    <dc:date>2024-06-03T11:21:28Z</dc:date>
    <item>
      <title>Classifying emails with SAS VTA and VDMML</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Classifying-emails-with-SAS-VTA-and-VDMML/m-p/930226#M10822</link>
      <description>&lt;P&gt;Hi everyone!&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I'm currently learning SAS programming, and I wanted to embark on my own project for now. I have access to SAS Viya, so I was thinking of conducting unsupervised classification of emails (multi-class classification) through VDMML and VTA.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I was thinking of running the text through VTA and then extracting the score code from the categories node, and then process this data to use in VDMML to train a classification model. However, I'm not sure what kind of pipeline would be suitable for this approach as most of the current pipelines seem catered towards supervised learning.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Any help in this area would be appreciated. Apologies if this is a very basic question, and thank&lt;/P&gt;</description>
      <pubDate>Thu, 30 May 2024 08:04:45 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Classifying-emails-with-SAS-VTA-and-VDMML/m-p/930226#M10822</guid>
      <dc:creator>thistleandtweed</dc:creator>
      <dc:date>2024-05-30T08:04:45Z</dc:date>
    </item>
    <item>
      <title>Re: Classifying emails with SAS VTA and VDMML</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Classifying-emails-with-SAS-VTA-and-VDMML/m-p/930597#M10823</link>
      <description>&lt;P&gt;I'm not so sure this is the best little project to learn SAS programming ... but anyway.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;In SAS terminology&amp;nbsp;&lt;SPAN&gt;multi-class classification (and multi-label&amp;nbsp;classification) are always supervised.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;You probably need&amp;nbsp;unsupervised learning &lt;STRONG&gt;clustering&lt;/STRONG&gt; classifiers or &lt;STRONG&gt;topic detection&lt;/STRONG&gt; capabilities.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;If there's no pipeline template for clustering in Model Studio (VDMML), you can always build such a pipeline yourself starting from a data node (or an empty pipeline).&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;SPAN&gt;After you have used Singular Value Decomposition (SVD) or&amp;nbsp;&lt;/SPAN&gt;Latent Dirichlet allocation (LDA) to reduce the dimensionality of the weighted term-by-document frequency matrix, you can perfectly apply some clustering algorithms. But every e-mail will belong to only 1 cluster. If you use the topic detection in VTA, then a single e-mail may contain several topics.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Koen&lt;/P&gt;
&lt;P&gt;&lt;LI-WRAPPER&gt;&lt;/LI-WRAPPER&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 03 Jun 2024 11:21:28 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Classifying-emails-with-SAS-VTA-and-VDMML/m-p/930597#M10823</guid>
      <dc:creator>sbxkoenk</dc:creator>
      <dc:date>2024-06-03T11:21:28Z</dc:date>
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