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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JDS</journal-id>
      <journal-title-group>
        <journal-title>Journal of Data Science</journal-title>
      </journal-title-group>
      <issn pub-type="epub">1680-743X</issn>
      <issn pub-type="ppub">1680-743X</issn>
      <publisher>
        <publisher-name>SOSRUC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">232_OK</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.201801_16(1).0005</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Determination of the Effective Economic and/or Demographic Indicators in Classification of European Union Member and Candidate Countries Using Partial Least Squares Discriminant Analysis</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Polat</surname>
            <given-names>Esra</given-names>
          </name>
        </contrib>
      </contrib-group>
      <volume>16</volume>
      <issue>1</issue>
      <fpage>79</fpage>
      <lpage>92</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Partial Least Squares Discriminant Analysis (PLSDA) is a statistical method for classification and consists of a classical Partial Least Squares Regression in which the dependent variable is a categorical one expressing the class membership of each observation. The aim of this study is both analyzing the performance of PLSDA method in classifying 28 European Union (EU) member countries and 7 candidate countries (Albania, Montenegro, Serbia, Macedonia FYR, Turkey moreover including potential candidates Bosnia and Herzegovina and Kosova) correctly to their pre-defined classes (candidate or member) and determining the economic and/or demographic indicators, which are effective in classifying, by using the data set obtained from database of the World Bank.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>classification</kwd>
        <kwd>demographic indicators</kwd>
        <kwd>economic indicators</kwd>
        <kwd>European Union</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
