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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Piché, R., Järvenpää, M., Turunen, E. et al. Bayesian analysis of GUHA hypotheses. J Intell Inf Syst 42, 47–73 (2014). https://doi.org/10.1007/s10844-013-0255-6
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DOI: https://doi.org/10.1007/s10844-013-0255-6