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Analysis of new variable selection methods for discriminant analysis

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  • Pacheco, Joaquin
  • Casado, Silvia
  • Nunez, Laura
  • Gomez, Olga

Abstract

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  • Pacheco, Joaquin & Casado, Silvia & Nunez, Laura & Gomez, Olga, 2006. "Analysis of new variable selection methods for discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1463-1478, December.
    • Handle: RePEc:eee:csdana:v:51:y:2006:i:3:p:1463-1478
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    References listed on IDEAS

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    1. Cristian Gatu & Erricos Kontoghiorghes, 2005. "Efficient strategies for deriving the subset VAR models," Computational Management Science, Springer, vol. 4(4), pages 253-278, November.
    2. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    3. Mladenovic, N. & Petrovic, J. & Kovacevic-Vujcic, V. & Cangalovic, M., 2003. "Solving spread spectrum radar polyphase code design problem by tabu search and variable neighbourhood search," European Journal of Operational Research, Elsevier, vol. 151(2), pages 389-399, December.
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    Cited by:

    1. Casado Yusta, Silvia & Nœ–ez Letamendía, Laura & Pacheco Bonrostro, Joaqu’n Antonio, 2018. "Predicting Corporate Failure: The GRASP-LOGIT Model || Predicci—n de la quiebra empresarial: el modelo GRASP-LOGIT," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 294-314, Diciembre.
    2. Unler, Alper & Murat, Alper, 2010. "A discrete particle swarm optimization method for feature selection in binary classification problems," European Journal of Operational Research, Elsevier, vol. 206(3), pages 528-539, November.
    3. Pacheco, Joaquín & Casado, Silvia & Núñez, Laura, 2009. "A variable selection method based on Tabu search for logistic regression models," European Journal of Operational Research, Elsevier, vol. 199(2), pages 506-511, December.
    4. Stąpor Katarzyna & Smolarczyk Tomasz & Fabian Piotr, 2016. "Heteroscedastic Discriminant Analysis Combined with Feature Selection for Credit Scoring," Statistics in Transition New Series, Statistics Poland, vol. 17(2), pages 265-280, June.
    5. Michael Fop & Pierre-Alexandre Mattei & Charles Bouveyron & Thomas Brendan Murphy, 2022. "Unobserved classes and extra variables in high-dimensional discriminant analysis," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(1), pages 55-92, March.
    6. Brusco, Michael J. & Steinley, Douglas, 2011. "Exact and approximate algorithms for variable selection in linear discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 123-131, January.
    7. Brusco, Michael J., 2014. "A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 38-53.
    8. Tomasz Smolarczyk & Katarzyna Stąpor & Piotr Fabian, 2016. "Heteroscedastic Discriminant Analysis Combined With Feature Selection For Credit Scoring," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 17(2), pages 265-280, June.
    9. Nkiet, Guy Martial, 2012. "Direct variable selection for discrimination among several groups," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 151-163.
    10. Pacheco, Joaquín & Casado, Silvia & Porras, Santiago, 2013. "Exact methods for variable selection in principal component analysis: Guide functions and pre-selection," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 95-111.
    11. Fouskakis, D., 2012. "Bayesian variable selection in generalized linear models using a combination of stochastic optimization methods," European Journal of Operational Research, Elsevier, vol. 220(2), pages 414-422.
    12. Cappozzo, Andrea & Greselin, Francesca & Murphy, Thomas Brendan, 2021. "Robust variable selection for model-based learning in presence of adulteration," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    13. Katarzyna Stąpor & Tomasz Smolarczyk & Piotr Fabian, 2016. "Heteroscedastic Discriminant Analysis Combined With Feature Selection For Credit Scoring," Statistics in Transition New Series, Polish Statistical Association, vol. 17(2), pages 265-280, June.

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