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Unbiased variable selection for classification trees with multivariate responses

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  • Lee, Tzu-Haw
  • Shih, Yu-Shan

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  • Lee, Tzu-Haw & Shih, Yu-Shan, 2006. "Unbiased variable selection for classification trees with multivariate responses," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 659-667, November.
    • Handle: RePEc:eee:csdana:v:51:y:2006:i:2:p:659-667
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    References listed on IDEAS

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    1. Kim H. & Loh W.Y., 2001. "Classification Trees With Unbiased Multiway Splits," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 589-604, June.
    2. Siciliano, Roberta & Mola, Francesco, 2000. "Multivariate data analysis and modeling through classification and regression trees," Computational Statistics & Data Analysis, Elsevier, vol. 32(3-4), pages 285-301, January.
    3. Nettleton, Dan & Banerjee, T., 2001. "Testing the equality of distributions of random vectors with categorical components," Computational Statistics & Data Analysis, Elsevier, vol. 37(2), pages 195-208, August.
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    Cited by:

    1. Hapfelmeier, A. & Ulm, K., 2014. "Variable selection by Random Forests using data with missing values," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 129-139.
    2. Ollech, Daniel & Webel, Karsten, 2020. "A random forest-based approach to identifying the most informative seasonality tests," Discussion Papers 55/2020, Deutsche Bundesbank.

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