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<Paper uid="W06-2604">
  <Title>Basque Country ccpzejaa@si.ehu.es I~naki Alegria UPV-EHU Basque Country acpalloi@si.ehu.es Olatz Arregi UPV-EHU Basque Country acparuro@si.ehu.es</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> In this paper we present a multiclassifier approach for multilabel document classificationproblems, whereasetofk-NNclassifiers is used to predict the category of text documents based on different training subsampling databases. These databases are obtained from the original training database by random subsampling. In order to combine the predictions generated by the multiclassifier, Bayesian voting is applied. Throughall theclassificationprocess,areduceddimensionvectorrepresen- null tation obtained by Singular Value Decomposition (SVD) is used for training and testingdocuments. Thegoodresultsofour experiments give an indication of the potentiality of the proposed approach.</Paragraph>
  </Section>
class="xml-element"></Paper>