SODA

A survey of Bayesian Data Mining - Part I: Discrete and semi-discrete Data Matrices

Arnborg, Stefan (1999) A survey of Bayesian Data Mining - Part I: Discrete and semi-discrete Data Matrices. [SICS Report]

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Abstract

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.

Item Type:SICS Report
Uncontrolled Keywords:Bayes Factor, Graphical Model, Mixture model, Dependency
ID Code:2246
Deposited By:Vicki Carleson
Deposited On:29 Oct 2007
Last Modified:18 Nov 2009 16:03

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