國家衛生研究院 NHRI:Item 3990099045/6341
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    题名: Split variable selection for tree modeling on rank data
    作者: Kung, YH;Lin, CT;Shih, YS
    贡献者: Division of Biostatistics and Bioinformatics
    摘要: A variable selection method for constructing decision trees with rank data is proposed. Itutilizes conditional independence tests based on loglinear models for contingency tables.Compared with other selection methods, our method is computationally more efficient.Moreover, our method is relatively unbiased and powerful in selecting the correct splitvariables. Simulation results and a real data study are given to demonstrate the strength ofour method.
    日期: 2012-09
    關聯: Computational Statistics and Data Analysis. 2012 Sep;56(9):2830-2836.
    Link to: http://dx.doi.org/10.1016/j.csda.2012.03.004
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0167-9473&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000304073600018
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84859911365
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