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A survey of Bayesian Data Mining - Part I: Discrete and semi-discrete Data Matrices
Number of Authors: 1
1999 (English)Report (Refereed)
Abstract [en]

This tutorial summarises the use of Bayesian analysis and Bayes factors for finding significant properties of discrete (categorical and ordinal) data. It overviews methods for finding dependencies and graphical models, latent variables, robust decision trees and association rules.

Place, publisher, year, edition, pages
Swedish Institute of Computer Science , 1999, 1. , 31 p.
Series
SICS Technical Report, ISSN 1100-3154 ; T99:08
Keyword [en]
Bayes Factor, Graphical Model, Mixture model, Dependency
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:ri:diva-21971OAI: oai:DiVA.org:ri-21971DiVA: diva2:1041513
Available from: 2016-10-31 Created: 2016-10-31

Open Access in DiVA

fulltext(317 kB)4 downloads
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Type fulltextMimetype application/pdf

Computer and Information Science

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ReferencesLink to record
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