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Stacked Regression With a Generalization of the Moore-Penrose Pseudoinverse

Author

Listed:
  • Górecki Tomasz

    (Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Umultowska 87, 61-614 Poznan, Poland .)

  • Łuczak Maciej

    (Faculty of Civil Engineering, Environmental and Geodetic Sciences, Koszalin University of Technology, Sniadeckich 2, 75-453 Koszalin, Poland .)

Abstract

In practice, it often happens that there are a number of classification methods. We are not able to clearly determine which method is optimal. We propose a combined method that allows us to consolidate information from multiple sources in a better classifier. Stacked regression (SR) is a method for forming linear combinations of different classifiers to give improved classification accuracy. The Moore-Penrose (MP) pseudoinverse is a general way to find the solution to a system of linear equations.

Suggested Citation

  • Górecki Tomasz & Łuczak Maciej, 2017. "Stacked Regression With a Generalization of the Moore-Penrose Pseudoinverse," Statistics in Transition New Series, Polish Statistical Association, vol. 18(3), pages 443-458, September.
    • Handle: RePEc:vrs:stintr:v:18:y:2017:i:3:p:443-458:n:6
    DOI: 10.21307/stattrans-2016-080
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    References listed on IDEAS

    as
    1. Michael Doumpos & Constantin Zopounidis, 2007. "Model combination for credit risk assessment: A stacked generalization approach," Annals of Operations Research, Springer, vol. 151(1), pages 289-306, April.
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