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» Extracting Propositions from Trained Neural Networks
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ESWA
2008
223views more  ESWA 2008»
13 years 7 months ago
Credit risk assessment with a multistage neural network ensemble learning approach
In this study, a multistage neural network ensemble learning model is proposed to evaluate credit risk at the measurement level. The proposed model consists of six stages. In the ...
Lean Yu, Shouyang Wang, Kin Keung Lai
NIPS
2007
13 years 8 months ago
A neural network implementing optimal state estimation based on dynamic spike train decoding
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...
ICAI
2008
13 years 8 months ago
A Tabu Based Neural Network Training Algorithm for Equalization of Communication Channels
: This paper presents a new approach to equalization of communication channels using Artificial Neural Networks (ANNs). A novel method of training the ANNs using Tabu based Back Pr...
Jitendriya Kumar Satapathy, Konidala Ratna Subhash...
KES
2008
Springer
13 years 7 months ago
Epileptic Seizure Classification Using Neural Networks with 14 Features
Epilepsy is one of the most frequent neurological disorders. The main method used in epilepsy diagnosis is electroencephalogram (EEG) signal analysis. However this method requires ...
Rui P. Costa, Pedro Oliveira, Guilherme Rodrigues,...
ICANN
2005
Springer
14 years 27 days ago
Batch-Sequential Algorithm for Neural Networks Trained with Entropic Criteria
The use of entropy as a cost function in the neural network learning phase usually implies that, in the back-propagation algorithm, the training is done in batch mode. Apart from t...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...