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An Empirical Comparison of Methods for Multi-label Data Stream Classification

  • Konstantina KarponiEmail author
  • Grigorios Tsoumakas
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 529)

Abstract

This paper studies the problem of multi-label classification in the context of data streams. We discuss related work in this area and present our implementation of several existing approaches as part of the Mulan software. We present empirical results on a real-world data stream concerning media monitoring and discuss and draw a number of conclusions regarding their performance.

Keywords

Multi-label learning Data streams Classification Media monitoring 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Aristotle University of ThessalonikiThessalonikiGreece

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