31 search results - page 1 / 7 » A low variance error boosting algorithm |
APIN
2010
13 years 5 months ago
2010
Abstract. This paper introduces a robust variant of AdaBoost, cwAdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with da...
ML
2000
ACM
13 years 4 months ago
2000
ACM
MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees. MultiBoosting can be viewed as combining AdaBoost with wagging. It is abl...
COLT
2006
Springer
13 years 8 months ago
2006
Springer
We propose a sequential randomized algorithm, which at each step concentrates on functions having both low risk and low variance with respect to the previous step prediction functi...
PAKDD
2000
ACM
13 years 8 months ago
2000
ACM
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...
IWBRS
2005
Springer
13 years 10 months ago
2005
Springer
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...