32 search results - page 2 / 7 » Dependency Bagging |
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Estimating the color of a scene illuminant often plays a central role in computational color constancy. While this problem has received significant attention, the methods that exi...
IDEAL
2007
Springer
13 years 11 months ago
2007
Springer
The dependence of the classification error on the size of a bagging ensemble can be modeled within the framework of Monte Carlo theory for ensemble learning. These error curves ar...
JMLR
2010
13 years 3 months ago
2010
Bagging is a simple way to combine estimates in order to improve their performance. This method, suggested by Breiman in 1996, proceeds by resampling from the original data set, c...
BMCBI
2010
13 years 4 months ago
2010
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
ACL
2009
13 years 2 months ago
2009
Iterative bootstrapping algorithms are typically compared using a single set of handpicked seeds. However, we demonstrate that performance varies greatly depending on these seeds,...