1 Ocak 2010 Dergi makalesi Açık Erişim

Guvenir, H. Altay; Cakir, Murat

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/28081</identifier>
  <creators>
    <creator>
      <creatorName>Guvenir, H. Altay</creatorName>
      <givenName>H. Altay</givenName>
      <familyName>Guvenir</familyName>
      <affiliation>Bilkent Univ, Dept Comp Engn, TR-06800 Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Cakir, Murat</creatorName>
      <givenName>Murat</givenName>
      <familyName>Cakir</familyName>
      <affiliation>Cent Bank Republ Turkey, Ankara, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Voting Features Based Classifier With Feature Construction And Its Application To Predicting Financial Distress</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2010</publicationYear>
  <dates>
    <date dateType="Issued">2010-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/28081</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1016/j.eswa.2009.06.037</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">Voting features based classifiers. shortly VFC. have been shown to perform well on most real-world data sets They are robust to irrelevant features and missing feature values. In this paper, we introduce an extension to VFC. called voting features based classifier with feature construction, VFCC for short, and show its application to the problem of predicting if a bank will encounter financial distress by analyzing, current financial statements. The previously developed VFC learn a set of rules that contain a single condition based on a single feature in their antecedent. The VFCC algorithm proposed in this work, oil the other hand, constructs rules whose antecedents may contain conjuncts based on several features. Experimental results on recent financial ratios of banks in Turkey show that the VFCC algorithm achieves better accuracy than other well-known rule learning classification algorithms (C) 2009 Elsevier Ltd. All rights reserved</description>
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