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  <title>DSpace Collection: IJSRD - International Journal for Scientific Research &amp; Development</title>
  <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/2161" />
  <subtitle>IJSRD - International Journal for Scientific Research &amp; Development</subtitle>
  <id>http://localhost:8080/xmlui/handle/123456789/2161</id>
  <updated>2026-06-23T06:34:02Z</updated>
  <dc:date>2026-06-23T06:34:02Z</dc:date>
  <entry>
    <title>Review on Multilabel Classification Algorithms</title>
    <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/2162" />
    <author>
      <name>Chaudhari, Ms. Prajakta C.</name>
    </author>
    <author>
      <name>Prof. Dr. S. S. Sane</name>
    </author>
    <id>http://localhost:8080/xmlui/handle/123456789/2162</id>
    <updated>2019-07-16T04:20:06Z</updated>
    <published>2016-02-01T00:00:00Z</published>
    <summary type="text">Title: Review on Multilabel Classification Algorithms
Authors: Chaudhari, Ms. Prajakta C.; Prof. Dr. S. S. Sane
Abstract: Multilabel classification is a framework in which&#xD;
each input data in training data set can be related to more&#xD;
than one class labels simultaneously. The goal of multilabel&#xD;
classification is to produce set of labels for unseen instances&#xD;
by analyzing training dataset. This paper presents&#xD;
fundamentals of multilabel classification, some multilabel&#xD;
classification algorithms and evaluation metrics</summary>
    <dc:date>2016-02-01T00:00:00Z</dc:date>
  </entry>
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