On the Parsimony of the Multi-Layer Perceptrons when Processing ...
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Erratum. On the Parsimony of the Multi-Layer Perceptrons when Processing Encoded Symbolic Variables. D. BONNET1, A. GRUMBACH1 and V. LABOUISSE2. 1 Départment ...
Bibliographic details on Erratum On the Parsimony of the Multi-Layer Perceptrons when Processing Encoded Symbolic Variables.
This article addresses the issue of symbolic processing with Multi-Layer Perceptrons through encoding. Given an encoding, we propose a lower bound of the number ...
Denis Bonnet, Alain Grumbach, Veronique Labouisse: Erratum On the Parsimony of the Multi-Layer Perceptrons when Processing Encoded Symbolic Variables. 201 ...
Erratum On the Parsimony of the Multi-Layer Perceptrons when Processing Encoded Symbolic Variables. Neural Process. Lett. 9(2): 201 (1999). [c13]. view.
Erratum On the Parsimony of the Multi-Layer Perceptrons when Processing Encoded Symbolic Variables. 201. Volume 9, Number 3, 1999. view. electronic edition via ...
This article addresses the issue of symbolic processing with Multi-Layer Perceptrons through encoding. Given an encoding, we propose a lower bound of the number ...
Denis Bonnet, Alain Grumbach, Veronique Labouisse: Erratum On the Parsimony of the Multi-Layer Perceptrons when Processing Encoded Symbolic Variables.
We use again the m variables coding but we use the weights of the modalities rather than 0 and 1's. 3.2 Recoding the inputs. Input data are recoded as explained ...
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Sep 21, 2021 · Multilayer Perceptron is a Neural Network algorithm that learns the relationships between linear and non-linear data.