4 search results - page 1 / 1 » Avoiding Boosting Overfitting by Removing Confusing Samples |
ECML
2007
Springer
13 years 11 months ago
2007
Springer
Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
FLAIRS
2006
13 years 6 months ago
2006
AdaBoost is a well known, effective technique for increasing the accuracy of learning algorithms. However, it has the potential to overfit the training set because its objective i...
TSMC
2008
13 years 4 months ago
2008
Abstract--Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security sy...
INTERSPEECH
2010
12 years 12 months ago
2010
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...