Bajesova mreža

Bajesova mreža (takođe poznat kao Bajesova mreža, Bajesov net, mreža verovanja ili mreža odluka) je probabilistički grafički model koji predstavlja skup promenljivih i njihovih uslovnih zavisnosti preko usmerenog acikličkog grafa (DAG).^[1] Iako je to jedan od nekoliko oblika kauzalne notacije, kauzalne mreže su posebni slučajevi Bajesovih mreža. Bajesove mreže su idealne za uzimanje događaja koji se dogodio i predviđanje verovatnoće da je bilo koji od nekoliko mogućih poznatih uzroka faktor koji doprinosi. Na primer, Bajesova mreža bi mogla da predstavlja verovatne odnose između bolesti i simptoma. S obzirom na simptome, mreža se može koristiti za izračunavanje verovatnoće prisustva različitih bolesti.

Efikasni algoritmi mogu da izvode zaključak i učenje u Bajesovim mrežama. Bajesove mreže koje modeliraju sekvence varijabli (npr. govornih signala ili proteinskih sekvenci) nazivaju se dinamičke Bajesove mreže. Generalizacije Bajesovih mreža koje mogu da predstavljaju i rešavaju probleme odlučivanja pod neizvesnošću nazivaju se dijagrami uticaja.

Reference

^ Ruggeri, Fabrizio; Kenett, Ron S.; Faltin, Frederick W., ур. (2007-12-14). Encyclopedia of Statistics in Quality and Reliability (на језику: енглески) (1 изд.). Wiley. стр. 1. ISBN 978-0-470-01861-3. doi:10.1002/9780470061572.eqr089.

Literatura

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Spoljašnje veze

An Introduction to Bayesian Networks and their Contemporary Applications Архивирано на сајту Wayback Machine (21. мај 2017)
On-line Tutorial on Bayesian nets and probability
Web-App to create Bayesian nets and run it with a Monte Carlo method
Continuous Time Bayesian Networks
Bayesian Networks: Explanation and Analogy
A live tutorial on learning Bayesian networks
A hierarchical Bayes Model for handling sample heterogeneity in classification problems, provides a classification model taking into consideration the uncertainty associated with measuring replicate samples.
Hierarchical Naive Bayes Model for handling sample uncertainty Архивирано 2007-09-28 на сајту Wayback Machine, shows how to perform classification and learning with continuous and discrete variables with replicated measurements.

[1] Ruggeri, Fabrizio; Kenett, Ron S.; Faltin, Frederick W., ур. (2007-12-14). Encyclopedia of Statistics in Quality and Reliability (на језику: енглески) (1 изд.). Wiley. стр. 1. ISBN 978-0-470-01861-3. doi:10.1002/9780470061572.eqr089.

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