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» Convergence of a Neural Network Classifier
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CEC
2009
IEEE
14 years 3 months ago
Evolving modular neural-networks through exaptation
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...
Jean-Baptiste Mouret, Stéphane Doncieux
FLAIRS
2004
13 years 10 months ago
A Method Based on RBF-DDA Neural Networks for Improving Novelty Detection in Time Series
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...
TNN
2010
234views Management» more  TNN 2010»
13 years 3 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
BMCBI
2010
149views more  BMCBI 2010»
13 years 9 months ago
A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context
Background: Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex eti...
Ioannis K. Valavanis, Stavroula G. Mougiakakou, Ke...
BMCBI
2004
205views more  BMCBI 2004»
13 years 9 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma