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Evaluating feature selection methods for learning in data mining applications

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  • Piramuthu, Selwyn

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  • Piramuthu, Selwyn, 2004. "Evaluating feature selection methods for learning in data mining applications," European Journal of Operational Research, Elsevier, vol. 156(2), pages 483-494, July.
  • Handle: RePEc:eee:ejores:v:156:y:2004:i:2:p:483-494
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    References listed on IDEAS

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    1. Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, vol. 38(7), pages 926-947, July.
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    Cited by:

    1. Aytug, Haldun, 2015. "Feature selection for support vector machines using Generalized Benders Decomposition," European Journal of Operational Research, Elsevier, vol. 244(1), pages 210-218.
    2. Verbeke, Wouter & Dejaeger, Karel & Martens, David & Hur, Joon & Baesens, Bart, 2012. "New insights into churn prediction in the telecommunication sector: A profit driven data mining approach," European Journal of Operational Research, Elsevier, vol. 218(1), pages 211-229.
    3. Abdelazim G. Hussien & Diego Oliva & Essam H. Houssein & Angel A. Juan & Xu Yu, 2020. "Binary Whale Optimization Algorithm for Dimensionality Reduction," Mathematics, MDPI, vol. 8(10), pages 1-24, October.
    4. Anzanello, Michel J. & Albin, Susan L. & Chaovalitwongse, Wanpracha A., 2012. "Multicriteria variable selection for classification of production batches," European Journal of Operational Research, Elsevier, vol. 218(1), pages 97-105.
    5. Cheng-Yu Ho & Ke-Sheng Cheng & Chi-Hang Ang, 2023. "Utilizing the Random Forest Method for Short-Term Wind Speed Forecasting in the Coastal Area of Central Taiwan," Energies, MDPI, vol. 16(3), pages 1-18, January.
    6. Juheng Zhang & Selwyn Piramuthu, 0. "Product recommendation with latent review topics," Information Systems Frontiers, Springer, vol. 0, pages 1-9.
    7. Ding‐Wen Tan & William Yeoh & Yee Ling Boo & Soung‐Yue Liew, 2013. "The Impact Of Feature Selection: A Data‐Mining Application In Direct Marketing," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(1), pages 23-38, January.
    8. Juheng Zhang & Selwyn Piramuthu, 2018. "Product recommendation with latent review topics," Information Systems Frontiers, Springer, vol. 20(3), pages 617-625, June.
    9. 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.
    10. Bodendorf, Frank & Xie, Qiao & Merkl, Philipp & Franke, Jörg, 2022. "A multi-perspective approach to support collaborative cost management in supplier-buyer dyads," International Journal of Production Economics, Elsevier, vol. 245(C).
    11. Crone, Sven F. & Lessmann, Stefan & Stahlbock, Robert, 2006. "The impact of preprocessing on data mining: An evaluation of classifier sensitivity in direct marketing," European Journal of Operational Research, Elsevier, vol. 173(3), pages 781-800, September.
    12. Lee, In Gyu & Yoon, Sang Won & Won, Daehan, 2022. "A Mixed Integer Linear Programming Support Vector Machine for Cost-Effective Group Feature Selection: Branch-Cut-and-Price Approach," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1055-1068.
    13. Bertolazzi, P. & Felici, G. & Festa, P. & Fiscon, G. & Weitschek, E., 2016. "Integer programming models for feature selection: New extensions and a randomized solution algorithm," European Journal of Operational Research, Elsevier, vol. 250(2), pages 389-399.
    14. Du, Wen Sheng & Hu, Bao Qing, 2018. "A fast heuristic attribute reduction approach to ordered decision systems," European Journal of Operational Research, Elsevier, vol. 264(2), pages 440-452.
    15. Gambella, Claudio & Ghaddar, Bissan & Naoum-Sawaya, Joe, 2021. "Optimization problems for machine learning: A survey," European Journal of Operational Research, Elsevier, vol. 290(3), pages 807-828.

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