Home > Table of Contents


Proceedings of the 2nd International Symposium on Information Processing (ISIP 2009)

Huangshan, China, August 21-23, 2009

Editors: Fei Yu, Jian Shu, and Guangxue Yue

AP Catalog Number: AP-PROC-CS-09CN002

ISBN: 978-952-5726-02-2 (Print), 978-952-5726-03-9 (CD-ROM)

Page(s): 428-432

Extensional Completed L-measure and Its Choquet Integral Regression Model

Hsiang-Chuan Liu, Chin-Chun Chen, Yu-Du Jheng, and Shih-Neng Wu

Full text: PDF


The well known fuzzy measures, λ-measure and P-measure, have only one formulaic solution. A multivalent fuzzy measure with infinitely many solutions based on P-measure was proposed by our previous work, called completed L-measure. In this paper, a further improved fuzzy measure, called extensional completed L-measure, is proposed. This new fuzzy measure is proved that it is not only an extension of completed L-measure but also can be considered as an extension of the λ-measure and P-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 extensional completed L-measure, completed L-measure, L-measure, λ-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 extensional completed L-measure based on γ-support outperforms others forecasting models.

Index Terms

λ-measure, P-measure, L-measure, completed L-measure, extensional completed L-measure

Copyright @ 2009 ACADEMY PUBLISHER All rights reserved