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http://asiair.asia.edu.tw/ir/handle/310904400/16617
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| Title: | Composed Fuzzy Measure of Maximized L-Measure and Delta-Measure |
| Authors: | 劉湘川;Liu, Hsiang-Chuan;Tsai, Hsien-Chang;Jheng, Yu-Du;Liu, Tung-Sheng |
| Contributors: | 生物與醫學資訊學系 |
| Keywords: | Lambda-measure;P-measure;Delta-measure;L-measure;composed fuzzy measure |
| Date: | 2010 |
| Issue Date: | 2012-11-23 17:15:08 (UTC+8) |
| Abstract: | "Abstract—The well known fuzzy measures, λ-measure and
P-measure, have only one formulaic solution. Two multivalent
fuzzy measures with infinitely many solutions, L-measure and
δ-measure, were proposed by our previous works, but the former
do not include the additive measure as the latter and the latter has
not so many measure solutions as the former, therefore, a
composed fuzzy measure of above two measures, called
Lδ
-measure was proposed by our additional previous work.
However, all of abovementioned fuzzy measures do not contain the
largest measure, B-measure, which all not completed measures. In
this paper, an improved completed fuzzy measure composed of
maximized L-measure and δ-measure, denoted L
mδ
-measure, is
proposed. For evaluating the Choquet integral regression models
with our proposed fuzzy measure and other different ones, two real
data experiments by using a 5-fold cross-validation mean square
error (MSE) were conducted. The performances of Choquet
integral regression models with fuzzy measure based L
mδ
-measure, L
mδ
-measure, Lδ
-measure, L-measure, δ-measure,
λ-measure, and P-measure, respectively, a ridge regression model,
and a multiple linear regression model are compared. Both of two
experimental results show that the Choquet integral regression
models with respect to our new measure based on γ-support
outperforms others forecasting models" |
| Relation: | WSEAS Transactions on Information Science and Applications |
| Appears in Collections: | [生物資訊與醫學工程學系 ] 期刊論文
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