Constraint Classification: A New Approach to Multiclass Classification

  • Sariel Har-Peled
  • Dan Roth
  • Dav Zimak
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2533)

Abstract

In this paper, we present a newviewof multiclass classification and introduce the constraint classification problem, a generalization that captures many flavors of multiclass classification. We provide the first optimal, distribution independent bounds for many multiclass learning algorithms, including winner-take-all (WTA). Based on our view, we present a learning algorithm that learns via a single linear classifier in high dimension. In addition to the distribution independent bounds, we provide a simple margin-based analysis improving generalization bounds for linear multiclass support vector machines.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Sariel Har-Peled
    • 1
  • Dan Roth
    • 1
  • Dav Zimak
    • 1
  1. 1.Department of Computer ScienceUniversity of IllinoisUrbana

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