BETTER ALTERNATIVES FOR STEPWISE DISCRIMINANT ANALYSIS

Authors

  • Katarzyna Stąpor Silesian Technical University Gliwice

DOI:

https://doi.org/10.18778/0208-6018.311.02

Keywords:

discriminant analysis, stepwise procedures, feature selection, metaheuristic, tabu search

Abstract

Discriminant Analysis can best be defined as a technique which allows the classification of an individual into several dictinctive populations on the basis of a set of measurements. Stepwise discriminant analysis (SDA) is concerned with selecting the most important variables whilst retaining the highest discrimination power possible. The process of selecting a smaller number of variables is often necessary for a variety number of reasons. In the existing statistical software packages SDA is based on the classic feature selection methods. Many problems with such stepwise procedures have been identified. In this work the new method based on the metaheuristic strategy tabu search will be presented together with the experimental results conducted on the selected benchmark datasets. The results are promising.

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Author Biography

Katarzyna Stąpor, Silesian Technical University Gliwice

Institute of Computer Science

professor

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Published

2016-01-07

How to Cite

Stąpor, K. (2016). BETTER ALTERNATIVES FOR STEPWISE DISCRIMINANT ANALYSIS. Acta Universitatis Lodziensis. Folia Oeconomica, 1(311). https://doi.org/10.18778/0208-6018.311.02

Issue

Section

MSA2015

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