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The Alpha-Procedure as an Inductive Approach to Pattern Recognition and Its Connection with Lorentz Transformation

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Advances in Intelligent Systems and Computing II (CSIT 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 689))

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Abstract

The paper deals with problems which appear when solving the task of pattern recognition in a feature space that is not identical with the space of the unknown decisive key features. In a common sense it deals with the correctness of solutions which are found in different coordinate systems. Even more, the opportunity of constructing a feature space for the final separation of classes by selecting the features in pairs, how it is done by the Alpha-procedure, will be investigated. Thereby, the problem of stability during the solving of pattern recognition tasks will be considered from the point of view of transformation groups. The possibility of avoiding the necessity of regularization by using the geometric equiaffine Lorentz transformation will be shown, exploiting for that aim as example the alpha-procedure.

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Authors and Affiliations

  1. University of Applied Sciences, 06217, Merseburg, Germany

    Tatjana Lange

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  1. Tatjana Lange
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Correspondence to Tatjana Lange .

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Editors and Affiliations

  1. Lviv Polytechnic National University, Lviv, Ukraine

    Natalia Shakhovska

  2. IRTC ITS NASU, Kiev, Ukraine

    Volodymyr Stepashko

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Lange, T. (2018). The Alpha-Procedure as an Inductive Approach to Pattern Recognition and Its Connection with Lorentz Transformation. In: Shakhovska, N., Stepashko, V. (eds) Advances in Intelligent Systems and Computing II. CSIT 2017. Advances in Intelligent Systems and Computing, vol 689. Springer, Cham. https://doi.org/10.1007/978-3-319-70581-1_20

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  • DOI: https://doi.org/10.1007/978-3-319-70581-1_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70580-4

  • Online ISBN: 978-3-319-70581-1

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