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Modified Score Function and Linear Weak Classifiers in LogitBoost Algorithm

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Image Processing and Communications (IP&C 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1062))

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Abstract

This paper presents a new extension of LogitBoost algorithm based on the distance of the object to the decision boundary, which is defined by the weak classifier used in boosting. In the proposed approach this distance is transformed by Gaussian function and defines the value of a score function. The assumed form of transforming functions means that the objects closest or farthest located from the decision boundary of the basic classifier have the lowest value of the scoring function. The described algorithm was tested on four data sets from UCI repository and compared with LogitBoost algorithm.

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Acknowledgments

This work was supported in part by the National Science Centre, Poland under the grant no. 2017/25/B/ST6/01750.

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Authors and Affiliations

  1. Faculty of Electronic, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Robert Burduk & Wojciech Bozejko

Authors
  1. Robert Burduk
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  2. Wojciech Bozejko
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Corresponding authors

Correspondence to Robert Burduk or Wojciech Bozejko .

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Editors and Affiliations

  1. Institute of Telecommunications and Computer Science, University of Science and Technology (UTP), Bydgoszcz, Poland

    Michał Choraś

  2. Department of Telecommunications, Computer Sciences and Electrical Engineering, University of Science and Technology (UTP), Bydgoszcz, Poland

    Ryszard S. Choraś

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Burduk, R., Bozejko, W. (2020). Modified Score Function and Linear Weak Classifiers in LogitBoost Algorithm. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications. IP&C 2019. Advances in Intelligent Systems and Computing, vol 1062. Springer, Cham. https://doi.org/10.1007/978-3-030-31254-1_7

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