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Multiclass SVM Classification Using Graphs Calibrated by Similarity between Classes

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Knowledge-Based and Intelligent Information and Engineering Systems (KES 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6884))

Abstract

In this paper new learning structures, similarity between classes based trees and directed acyclic graph, are presented. The proposed structures are based on a distribution of recognized classes in a data space, unlike the known graph methods such as the tree based One–Against–All (OAA) algorithm or the directed acyclic graph based One–Against–One (OAO) algorithm. The structures are created by grouping similar classes. The similarity between classes is estimated by a distance between classes. The OAO strategy is implemented only for the nearest classes. In other cases the OAA strategy is used. This method allows reduction of the classification costs without a significant growth of the classification error.

Algorithms, which create similarity based trees and directed acyclic graph are presented in this paper. These methods are also compared in digits recognition task with existing ones.

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Author information

Authors and Affiliations

  1. Faculty of Mathematics and Information Science, Warsaw University of Technology, pl. Politechniki 1, 00-661, Warsaw, Poland

    Marcin Luckner

Authors
  1. Marcin Luckner
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Editors and Affiliations

  1. Institute of Integrated Sensor Systems, University of Kaiserslautern, Erwin-Schroedinger-str. 12, 67663, Kaiserslautern, Germany

    Andreas König

  2. Knowledge-Based Systems Group, Department of Computer Science, University of Kaiserslautern, P.O. Box 3049, 67653, Kaiserslautern, Germany

    Andreas Dengel

  3. School of Business, University of Applied Sciences Northwestern Switzerland, Riggenbachstr. 16, 4600, Olten, Switzerland

    Knut Hinkelmann

  4. Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, 599-8531, Sakai, Osaka, Japan

    Koichi Kise

  5. KES International, P.O. Box 2115, BN43 9AF, Shoreham-by-sea, UK

    Robert J. Howlett

  6. University of South Australia, Adelaide, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2011 Springer-Verlag Berlin Heidelberg

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Luckner, M. (2011). Multiclass SVM Classification Using Graphs Calibrated by Similarity between Classes. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6884. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23866-6_46

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  • DOI: https://doi.org/10.1007/978-3-642-23866-6_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23865-9

  • Online ISBN: 978-3-642-23866-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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