All
All

What are you looking for?

All
Projects
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Comparative study of noisy-max nodes and general nodes in Bayesian network models

Result 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.

Keywords

ValidationStructural learningSensitivity analysisNoisy-MAX nodesGross Domestic Product (GDP)General nodesBayesian networks

The result's identifiers

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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • 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

  • ISSN

    1613-0073

  • e-ISSN

  • 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

Result type

D - Article in proceedings

D

OECD FORD

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Year of implementation

2020