交叉验证法在模型选择中的应用——以OLS和RR为例
Application of Cross-Validation in Model Selection—Take OLS and RR as Examples
DOI: 10.12677/SA.2019.81004, PDF,   
作者: 曹延姗*：云南财经大学，云南 昆明
关键词: 交叉验证；最小二乘估计；岭回归；模型选择； Cross-Validation； OLS； RR； Model Selection
摘要: 文章回顾了交叉验证法的起源及发展，对已有研究成果进行总结和归纳。在此基础上，选择其中较为常用的留一交叉验证法对实例进行模型选择。分别采用最小二乘估计法和岭回归法对乙炔的反应数据进行分析，建立相应的模型，并对所建立的模型进行选择，同时探讨选择的合理性及现实性。
Abstract: This paper reviews the origin and development of cross-validation, and summarizes the previous research results. On this basis, leave-one-out cross-validation is used to solve some problems for model selection. OLS and RR were used to analyze the reaction of acetylene data, establishing appropriate models and selecting the optimal model. At the same time, the rationality and reality of the model selection were discussed.
文章引用：曹延姗. 交叉验证法在模型选择中的应用——以OLS和RR为例[J]. 统计学与应用, 2019, 8(1): 26-30. https://doi.org/10.12677/SA.2019.81004

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