89 search results - page 2 / 18 » Using Validation Sets to Avoid Overfitting in AdaBoost |
ICMLA
2004
13 years 6 months ago
2004
AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...
TSMC
2008
13 years 5 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...
FGR
2004
IEEE
13 years 9 months ago
2004
IEEE
An extension of the AdaBoost learning algorithm is proposed and brought to bear on the face detection problem. In each weak classifier selection cycle, the novel totally correctiv...
TNN
2008
13 years 5 months ago
2008
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
AIA
2007
13 years 6 months ago
2007
In this paper, a novel and effective criterion based on the estimation of the signal-to-noise-ratio figure (SNRF) is proposed to optimize the number of hidden neurons in neural ne...