45 search results - page 4 / 9 » Boosting in the Limit: Maximizing the Margin of Learned Ense... |
IJCAI
2003
13 years 9 months ago
2003
Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
ICDM
2009
IEEE
14 years 2 months ago
2009
IEEE
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
COLT
2001
Springer
14 years 6 days ago
2001
Springer
The notion of embedding a class of dichotomies in a class of linear half spaces is central to the support vector machines paradigm. We examine the question of determining the mini...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
Boosting algorithms build highly accurate prediction mechanisms from a collection of lowaccuracy predictors. To do so, they employ the notion of weak-learnability. The starting po...
MCS
2002
Springer
13 years 7 months ago
2002
Springer
Abstract. Boosting methods are known to improve generalization performances of learning algorithms reducing both bias and variance or enlarging the margin of the resulting multi-cl...