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Unbiased variable selection for classification trees with multivariate responses

机译:具有多变量响应的分类树的无偏变量选择

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摘要

A variable selection scheme is proposed for constructing multivariate classification trees. It utilizes conditional independence test derived from hierarchical loglinear model for three-way contingency table to control selection bias. Furthermore, it is compared with some existing selection methods in terms of selection power. Simulation results show that our method is unbiased and has better selection power.
机译:提出了一种用于构建多元分类树的变量选择方案。它利用从分层对数线性模型得出的条件独立性测试对三向列联表进行控制,以控制选择偏差。此外,就选择能力而言,它与一些现有的选择方法进行了比较。仿真结果表明,该方法是无偏的,具有较好的选择能力。

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