Choquet Integral with Respect to Sigma-Fuzzy Measure

被引:0
|
作者
Liu, Hsiang-Chuan [1 ]
Wu, Der-Bang [2 ]
Jheng, Yu-Du [3 ]
Chen, Chin-Chun [4 ]
Chien, Maw-Fa [5 ]
Sheu, Tian-Wei [6 ]
机构
[1] Asia Univ, Dept Bioinformat, Wufeng 41354, Taichung County, Taiwan
[2] Taichung Univ, Dept Math Educ, Grad Inst Educ Measurement Statist, Taichung 40306, Taiwan
[3] Univ Asia, Grad Inst Educ Measurement Statist, Taichung 40306, Taiwan
[4] Min Coll, Dept Gen Educ, Tainan 736, Taiwan
[5] Coll Entrace Examinat Ctr, Dept Mesarement & Statist, Taipei 10099, Taiwan
[6] Taichung Univ, Grad Inst Educ Measurement & Statist, Taichung 40306, Taiwan
关键词
lambda-measure; P-measure; sigma-measure; gamma-support; Choquet integral regression model;
D O I
10.1109/ICMA.2009.5246540
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Both the well known fuzzy measures, lambda-measure and P-measure, have only one formulaic solution, the former is not a closed form, and the latter not sensitive enough. In this paper, A novel multivalent fuzzy measure with infinitely many solutions, called sigma-measure, is proposed. This new measure can be considered as an extension of the P. measure and lambda- measure, For evaluating the Choquet integral regression models with our proposed fuzzy measure and other different ones, a real data experiment by using a 5-fold cross-validation mean square error (MSE) is conducted. The performances of Choquet integral regression models with fuzzy measure based on a-measure. lambda-measure and P-measure, respectively, a ridge regression model and a multiple linear regression model are compared. Experimental result shows that the Choquet integral regression models with respect to sigma-measure based on gamma-support outperforms other forecasting models.
引用
收藏
页码:1223 / +
页数:3
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