ML
2007
ACM
13 years 3 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 ...
ML
2002
ACM
13 years 4 months ago
2002
ACM
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
ML
2002
ACM
13 years 4 months ago
2002
ACM
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
JMLR
2002
13 years 4 months ago
2002
We construct a framework which allows an algorithm to turn the distributions produced by some boosting algorithms into polynomially smooth distributions (w.r.t. the PAC oracle...
CORR
2000
Springer
13 years 4 months ago
2000
Springer
In this paper Schapire and Singer's AdaBoost.MH boosting algorithm is applied to the Word Sense Disambiguation (WSD) problem. Initial experiments on a set of 15 selected polys...
PRL
2008
13 years 4 months ago
2008
Boosting is a set of methods for the construction of classifier ensembles. The differential feature of these methods is that they allow to obtain a strong classifier from the comb...
NECO
2006
13 years 4 months ago
2006
The application of boosting technique to the regression problems has received relatively little attention in contrast to the research aimed at classification problems. This paper ...
JMLR
2006
13 years 4 months ago
2006
We give a review of various aspects of boosting, clarifying the issues through a few simple results, and relate our work and that of others to the minimax paradigm of statistics. ...
COMSIS
2006
13 years 4 months ago
2006
In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of ...
AAAI
1996
13 years 5 months ago
1996
Breiman's bagging and Freund and Schapire's boosting are recent methods for improving the predictive power of classi er learning systems. Both form a set of classi ers t...