417 search results - page 3 / 84 » Some Theory for Generalized Boosting Algorithms |
ECAI
2006
Springer
13 years 9 months ago
2006
Springer
Scaling discrete AdaBoost to handle real-valued weak hypotheses has often been done under the auspices of convex optimization, but little is generally known from the original boost...
ALT
2006
Springer
14 years 2 months ago
2006
Springer
Abstract. We propose a thresholded ensemble model for ordinal regression problems. The model consists of a weighted ensemble of confidence functions and an ordered vector of thres...
CSB
2004
IEEE
13 years 9 months ago
2004
IEEE
Boosted PRIM (Patient Rule Induction Method) is a new algorithm developed for two-class classification problems. PRIM is a variation of those Tree-Based methods ( [4] Ch9.3), seek...
COLT
2008
Springer
13 years 7 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...
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...