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ESWA
2008
223views more  ESWA 2008»
13 years 7 months ago
Credit risk assessment with a multistage neural network ensemble learning approach
In this study, a multistage neural network ensemble learning model is proposed to evaluate credit risk at the measurement level. The proposed model consists of six stages. In the ...
Lean Yu, Shouyang Wang, Kin Keung Lai
HIS
2004
13 years 9 months ago
Classification Ensembles for Shaft Test Data: Empirical Evaluation
: A-scans from ultrasonic testing of long shafts are complex signals. The discrimination of different types of echoes is of importance for non-destructive testing and equipment mai...
Kyungmi Lee, Vladimir Estivill-Castro
TNN
2008
124views more  TNN 2008»
13 years 7 months ago
Just-in-Time Adaptive Classifiers - Part II: Designing the Classifier
Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolu...
Cesare Alippi, Manuel Roveri
ACL
2006
13 years 9 months ago
Semantic Parsing with Structured SVM Ensemble Classification Models
We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection metho...
Minh Le Nguyen, Akira Shimazu, Xuan Hieu Phan
SOCO
2007
Springer
14 years 1 months ago
Dynamic Contextual Service Ranking
This paper explores service composition in pervasive environments with a focus on dynamic service selection. Service orientation offers the dynamism and loose coupling needed in pe...
André Bottaro, Richard S. Hall