Title :
Choquet integral with respect to sigma-fuzzy measure
Author :
Liu, Hsiang-chuan ; Jheng, Yu-Du ; Chien, Maw-Fa ; Wu, Der-Bang ; Chen, Chin-chun ; Sheu, Tian-Wei
Author_Institution :
Dept. of Bioinf., Asia Univ., Wufeng, Taiwan
Abstract :
Both the well known fuzzy measures, ¿-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 ¿-measure, is proposed. This new measure can be considered as an extension of the P-measure and ¿-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 ¿-measure, ¿-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 ¿-measure based on ¿-support outperforms other forecasting models.
Keywords :
fuzzy set theory; integral equations; mean square error methods; regression analysis; Choquet integral regression model; P-measure; mean square error method; multiple linear regression model; multivalent fuzzy measure; ridge regression model; sigma-fuzzy measure; ¿-measure; Asia; Automation; Bioinformatics; Cities and towns; Educational institutions; Fuzzy sets; Linear regression; Mean square error methods; Predictive models; Statistics; γ-support; λ-measure; σ-measure; Choquet integral regression model; P-measure;
Conference_Titel :
Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-2692-8
Electronic_ISBN :
978-1-4244-2693-5
DOI :
10.1109/ICMA.2009.5246540