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A New Tool for Feature Extraction and Its Application to Credit Risk Analysis

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  • First Online:
New State of MCDM in the 21st Century

Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 648))

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Abstract

The aim of this paper is to present a new feature extraction method. Our method is an extension of the classical Partial Least Squares (PLS) algorithm. However, a new weighted separation criterion is applied which is based on the within and between scatter matrices. In order to compare the performance of the classification the economical datasets are used.

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Notes

  1. 1.

    http://archive.ics.uci.edu/ml/

  2. 2.

    http://www.csie.ntu.edu.tw/~cjlin/libsvm

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Author information

Authors and Affiliations

  1. Institute of Mathematics, University of Silesia, 14 Bankowa Street, 40-007, Katowice, Poland

    Paweł Błaszczyk

Authors
  1. Paweł Błaszczyk
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Corresponding author

Correspondence to Paweł Błaszczyk .

Editor information

Editors and Affiliations

  1. Research Cntr on Fict. Econ. & Data Sci., Chinese Academy of Sciences, Zhongguancun East Road, No 80 Building 6, Room 203, Beijing, 10090, China, People's Republic

    Yong Shi

  2. College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE 68182, USA

    Yong Shi

  3. Academy of Mathematics and, Chinese Academy of Sciences, Zhonguancun East Road 55Haidian, Beijing, NE, 100190, China, People's Republic

    Shouyang Wang

  4. School of Management and Economics, University of Electr. Science & Technol., Zhonguancun East Road No. 55, Haidian, Chengdu, 610054, China, People's Republic

    Gang Kou PhD

  5. Aalto University School of Economics, 21210, 00076, Aalto, Finland

    Jyrki Wallenius

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© 2011 Springer-Verlag Berlin Heidelberg

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Błaszczyk, P. (2011). A New Tool for Feature Extraction and Its Application to Credit Risk Analysis. In: Shi, Y., Wang, S., Kou, G., Wallenius, J. (eds) New State of MCDM in the 21st Century. Lecture Notes in Economics and Mathematical Systems, vol 648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19695-9_11

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