How to Improve the Generalization Ability of Multi-layer Neural Networks.
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F02%3A06020032" target="_blank" >RIV/67985807:_____/02:06020032 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
How to Improve the Generalization Ability of Multi-layer Neural Networks.
Original language description
The generalization ability of MNN will usually increase when the number of parameters, modified during the training process will decrease. We present an approach, based on the mathematical logic paradigms for the selection of significant input parameters, which are the most important from the point of view of output parameters. These parameters are later used for the training of multi-layer neural networks.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BA - General mathematics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2002
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
The 6th World Multi-Conference on Systemics, Cybernetics and Informatics. Proceedings.
ISBN
980-07-8150-1
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1-6
Publisher name
IIIS
Place of publication
Orlando
Event location
Orlando [US]
Event date
Jul 14, 2002
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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