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CORR
2010
Springer
150views Education» more  CORR 2010»
15 years 1 months ago
Extraction of Symbolic Rules from Artificial Neural Networks
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...
S. M. Kamruzzaman, Md. Monirul Islam
IJCAI
1997
15 years 3 months ago
Extracting Propositions from Trained Neural Networks
This paper presents an algorithm for extract­ ing propositions from trained neural networks. The algorithm is a decompositional approach which can be applied to any neural networ...
Hiroshi Tsukimoto
121
Voted
IJCAI
2007
15 years 3 months ago
A Fully Connectionist Model Generator for Covered First-Order Logic Programs
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
Sebastian Bader, Pascal Hitzler, Steffen Höll...
TNN
2010
234views Management» more  TNN 2010»
14 years 8 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
2005
126views more  BMCBI 2005»
15 years 1 months ago
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA struc...
Robert G. Beiko, Robert L. Charlebois