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On the Impact of Distance Metrics in Instance-Based Learning Algorithms

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Pattern Recognition and Image Analysis (IbPRIA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9117))

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Abstract

In this paper we analyze the impact of distinct distance metrics in instance-based learning algorithms. In particular, we look at the well-known 1-Nearest Neighbor (NN) algorithm and the Incremental Hypersphere Classifier (IHC) algorithm, which proved to be efficient in large-scale recognition problems and online learning. We provide a detailed empirical evaluation on fifteen datasets with several sizes and dimensionality. We then statistically show that the Euclidean and Manhattan metrics significantly yield good results in a wide range of problems. However, grid-search like methods are often desirable to determine the best matching metric depending on the problem and algorithm.

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Acknowledgments

This work is partly funded by iCIS (CENTRO-07-ST24-FEDER-002003).

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Authors and Affiliations

  1. UDI, Polytechnic of Guarda, Guarda, Portugal

    Noel Lopes

  2. Department of Informatics Engineering, CISUC, University of Coimbra, Coimbra, Portugal

    Noel Lopes & Bernardete Ribeiro

Authors
  1. Noel Lopes
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  2. Bernardete Ribeiro
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Corresponding author

Correspondence to Noel Lopes .

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Editors and Affiliations

  1. Universitat Politècnica de València, València, Spain

    Roberto Paredes

  2. Universidade do Porto, Porto, Portugal

    Jaime S. Cardoso

  3. Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Xosé M. Pardo

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Lopes, N., Ribeiro, B. (2015). On the Impact of Distance Metrics in Instance-Based Learning Algorithms. In: Paredes, R., Cardoso, J., Pardo, X. (eds) Pattern Recognition and Image Analysis. IbPRIA 2015. Lecture Notes in Computer Science(), vol 9117. Springer, Cham. https://doi.org/10.1007/978-3-319-19390-8_6

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  • DOI: https://doi.org/10.1007/978-3-319-19390-8_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19389-2

  • Online ISBN: 978-3-319-19390-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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