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» Regularized Learning with Networks of Features
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ICANN
2001
Springer
15 years 4 months ago
Feature Extraction Using ICA
In manipulating data such as in supervised learning, we often extract new features from original features for the purpose of reducing the dimensions of feature space and achieving ...
Nojun Kwak, Chong-Ho Choi, Jin-Young Choi
TNN
2008
119views more  TNN 2008»
14 years 11 months ago
Selecting Useful Groups of Features in a Connectionist Framework
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
Debrup Chakraborty, Nikhil R. Pal
IJCNN
2008
IEEE
15 years 6 months ago
A formula of equations of states in singular learning machines
Abstract— Almost all learning machines used in computational intelligence are not regular but singular statistical models, because they are nonidentifiable and their Fisher info...
Sumio Watanabe
TNN
2008
79views more  TNN 2008»
14 years 11 months ago
Performing Feature Selection With Multilayer Perceptrons
An experimental study on two decision issues for wrapper feature selection (FS) with multilayer perceptrons and the sequential backward selection (SBS) procedure is presented. The ...
Enrique Romero, Josep M. Sopena
PRL
1998
93views more  PRL 1998»
14 years 11 months ago
A connectionist method for pattern classification with diverse features
A novel connectionist method is proposed to simultaneously use diverse features in an optimal way for pattern classification. Unlike methods of combining multiple classifiers, a m...
Ke Chen 0001