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Journal of Intelligent Information Systems

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01-02-2014

Bayesian analysis of GUHA hypotheses

Authors: Robert Piché, Marko Järvenpää, Esko Turunen, Milan Šimůnek

Published in: Journal of Intelligent Information Systems | Issue 1/2014

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Abstract

The LISp-Miner system for data mining and knowledge discovery uses the GUHA method to comb through a large data base and finds 2 × 2 contingency tables that satisfy a certain condition given by generalised quantifiers and thereby suggest the existence of possible relations between attributes. In this paper, we show how a more detailed interpretation of the data in the tables that were found by GUHA can be obtained using Bayesian statistical methods. Using a multinomial sampling model and Dirichlet prior, we derive posterior distributions for parameters that correspond to GUHA generalised quantifiers. Examples are presented illustrating the new Bayesian post-processing tools implemented in LISp-Miner. A statistical model for the analysis of contingency tables for data from two subpopulations is also presented.

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Title: Bayesian analysis of GUHA hypotheses
Authors: Robert Piché
Marko Järvenpää
Esko Turunen
Milan Šimůnek
Publication date: 01-02-2014
Publisher: Springer US
Published in: Journal of Intelligent Information Systems / Issue 1/2014
Print ISSN: 0925-9902
Electronic ISSN: 1573-7675
DOI: https://doi.org/10.1007/s10844-013-0255-6

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