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PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
14 years 3 days ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
IJCNN
2008
IEEE
14 years 3 months ago
Product design model for impact toughness estimation in steel plate manufacturing
— The purpose of this study was to develop a product design model for impact toughness estimation of low-alloy steel plates. Based on these estimates, the rejection probability o...
Satu Tamminen, Ilmari Juutilainen, Juha Rönin...
NECO
2006
157views more  NECO 2006»
13 years 8 months ago
Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression
The application of boosting technique to the regression problems has received relatively little attention in contrast to the research aimed at classification problems. This paper ...
Durga L. Shrestha, Dimitri P. Solomatine
ACMICEC
2008
ACM
270views ECommerce» more  ACMICEC 2008»
13 years 10 months ago
Adaptive strategies for predicting bidding prices in supply chain management
Supply Chain Management (SCM) involves a number of interrelated activities from negotiating with suppliers to competing for customer orders and scheduling the manufacturing proces...
Yevgeniya Kovalchuk, Maria Fasli
ECAI
2010
Springer
13 years 6 months ago
Continuous Conditional Random Fields for Regression in Remote Sensing
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
Vladan Radosavljevic, Slobodan Vucetic, Zoran Obra...