Overview of Bayesian Network

Language: English

Published by LAP LAMBERT Academic Publishing, 2022

6204744402 / 9786204744407

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Bayesian network is a combination of probabilistic model and graph model. It is applied widely in machine learning, data mining, diagnosis, etc. because it has a solid evidence-based inference which is familiar to human intuition. However, Bayesian network may cause confusions because there are many complicated concepts, formulas and diagrams relating to it. Such concepts should be organized and presented in such a clear manner that understanding it is easy. This is the goal of this report. The report includes 5 main sections that cover principles of Bayesian network. The section 1 is an introduction to Bayesian network giving some basic concepts. Advanced concepts are mentioned in section 2. Inference mechanism of Bayesian network is described in section 3. Parameter learning which tells us how to update parameters of Bayesian network is described in section 4. Section 5 focuses on structure learning which mentions how to build up Bayesian network. In general, three main subjects of Bayesian network are inference, parameter learning, and structure learning which are mentioned in successive sections 3, 4, and 5. Section 6 is the conclusion.

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Title
Overview of Bayesian Network
Author
Loc Nguyen
Publisher
LAP LAMBERT Academic Publishing
Publication year
2022
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6204744402
ISBN 13
9786204744407
Item weight
179 grams
Dimensions
220x150x7 mm

AHA-BUCH GmbH

Einbeck, Germany

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