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AAAI
1998
13 years 9 months ago
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
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...
Adam J. Grove, Dale Schuurmans
TSMC
2008
172views more  TSMC 2008»
13 years 7 months ago
AdaBoost-Based Algorithm for Network Intrusion Detection
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...
Weiming Hu, Wei Hu, Stephen J. Maybank
KAIS
2010
144views more  KAIS 2010»
13 years 6 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
ICPR
2010
IEEE
13 years 5 months ago
Boosting Bayesian MAP Classification
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...
ECCV
2008
Springer
14 years 9 months ago
3D Face Recognition by Local Shape Difference Boosting
Abstract. A new approach, called Collective Shape Difference Classifier (CSDC), is proposed to improve the accuracy and computational efficiency of 3D face recognition. The CSDC le...
Yueming Wang, Xiaoou Tang, Jianzhuang Liu, Gang Pa...