Comparative study of noisy-max nodes and general nodes in Bayesian network models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F20%3A43895560" target="_blank" >RIV/44555601:13440/20:43895560 - 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
Comparative study of noisy-max nodes and general nodes in Bayesian network models
Original language description
This article is devoted to the use of Bayesian networks for analyzing the growth of gross domestic product (GDP) of Ukraine and offers a comparative description of the use of various structural learning algorithms. A comparative study of the behavior of the Noisy-MAX nodes and the General nodes in the design of the Bayesian network was carried out. It has been shown that Noisy-max nodes in comparison with General nodes provide a relatively high initial accuracy. General nodes require retesting. However, Noisy-MAX nodes entail an increase in time and computational cost. (C) 2020 for this paper by its authors.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
CEUR Workshop Proceedings
ISBN
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ISSN
1613-0073
e-ISSN
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Number of pages
11
Pages from-to
56-66
Publisher name
CEUR-WS
Place of publication
Německo
Event location
Lviv
Event date
Apr 23, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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