基于SVM和粗糙集理论的董事会效率评价研究

被引:4
作者
张大光
机构
[1] 北京航空航天大学经济管理学院
关键词
董事会效率; 多分类; 支持向量机; 粗糙集; 指标选择;
D O I
暂无
中图分类号
F276.6 [公司]; F224 [经济数学方法];
学科分类号
1202 ; 120202 ; 0701 ; 070104 ;
摘要
本文构建了影响董事会效率的指标体系,并首次采用支持向量机方法(SVM)建立了董事会效率评价的五级分类模型,通过粗糙集理论的属性约简方法来确定最优的输入指标组合。实验结果表明,本文建立的董事会效率评价模型的判别精度要优于已有模型,而通过对惩罚矩阵的合理调整,模型的判别精度可以进一步提高。
引用
收藏
页码:181 / 186
页数:6
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