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Global and Local Rejection Option in Multi–classification Task

  • Marcin Luckner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8681)

Abstract

This work presents two rejection options. The global rejection option separates the foreign observations – not defined in the classification task – from the normal observations. The local rejection option works after the classification process and separates observations individually for each class. We present implementation of both methods for binary classifiers grouped in a graph structure (tree or directed acyclic graph). Next, we prove that the quality of rejection is identical for both options and depends only on the quality of binary classifiers. The methods are compared on the handwritten digits recognition task. The local rejection option works better for the most part.

Keywords

Rejection Option Support Vector Machines Graph Ensemble Pattern Recognition 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Marcin Luckner
    • 1
  1. 1.Faculty of Mathematics and Information ScienceWarsaw University of TechnologyWarszawaPoland

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