32 search results - page 2 / 7 » Dependency Bagging |
CVPR
2008
IEEE
15 years 11 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
15 years 3 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
14 years 8 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...
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BMCBI
2010
14 years 9 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
14 years 7 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,...