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Team ULjubljana’s Solution to the JRS 2012 Data Mining Competition

  • Jure Zbontar
  • Marinka Zitnik
  • Miha Zidar
  • Gregor Majcen
  • Matic Potocnik
  • Blaz Zupan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7413)

Abstract

The task of the JRS 2012 data mining competition was to infer a prediction model capable of associating biomedical journal articles with a subset of topics. Our approach consisted of training a set of base learners, stacking their results, and thresholding the predictions on each label separately. Our method obtained an F-score of 0.53579, which was enough to claim first prize in the competition.

Keywords

multi-label classification topical classification sparse datasets stacking 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jure Zbontar
    • 1
  • Marinka Zitnik
    • 1
  • Miha Zidar
    • 1
  • Gregor Majcen
    • 1
  • Matic Potocnik
    • 1
  • Blaz Zupan
    • 1
  1. 1.Faculty of Computer and Information ScienceUniversity of LjubljanaLjubljanaSlovenia

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