9 search results - page 1 / 2 » Boosting the margin: A new explanation for the effectiveness... |
ICML
1997
IEEE
14 years 5 months ago
1997
IEEE
COLT
2008
Springer
13 years 6 months ago
2008
Springer
Much attention has been paid to the theoretical explanation of the empirical success of AdaBoost. The most influential work is the margin theory, which is essentially an upper bou...
AAAI
1998
13 years 6 months ago
1998
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
ECML
2004
Springer
13 years 10 months ago
2004
Springer
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
ML
2007
ACM
13 years 4 months ago
2007
ACM
AdaBoost.OC has been shown to be an effective method in boosting “weak” binary classifiers for multi-class learning. It employs the Error-Correcting Output Code (ECOC) method ...