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Strategies defined for the development of applications using Multilayer Perceptrons: A survey
Author(s) -
PérezMiñana Elena,
Ross Peter
Publication year - 1996
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.1996.tb00185.x
Subject(s) - computer science , perceptron , representation (politics) , multilayer perceptron , artificial intelligence , machine learning , task (project management) , set (abstract data type) , context (archaeology) , data mining , domain (mathematical analysis) , artificial neural network , paleontology , mathematical analysis , mathematics , management , politics , political science , law , economics , biology , programming language
The success in developing an application employing the Multilayer perceptron (MLP) as knowledge representation form is very dependent on the degree of complexity that the structure of the application's domain has. Different mathematical and/or statistical techniques have been developed to subtract the maximum amount of information of this type from an available sample of the operating space associated to the task of interest. In the context of MLP it has been used to decide on the form the different intervening parameters of the network and/or related learning algorithm (LA) should have. This paper provides an overview of the processes that have been defined to generate network applications using the MLP model, giving particular attention to those based on the dynamic creation of a network's architecture through the application of different techniques for subtracting information about the operating domain in which the training set is subsumed.