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- W2076310205 abstract "Abstract The purpose of this article is to show that Bayesian methods, coupled with Markov chain Monte Carlo computational techniques, can be successfully employed in the analysis of highly dimensional complex datasets, such as those occurring in data mining applications. Our methodology employs conditional independence graphs to localize model specification and inferences, thus allowing a considerable gain in flexibility of modelling and efficiency of the computations. Copyright © 2001 John Wiley & Sons, Ltd." @default.
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- W2076310205 date "2001-01-01" @default.
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- W2076310205 title "Bayesian data mining, with application to benchmarking and credit scoring" @default.
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- W2076310205 doi "https://doi.org/10.1002/asmb.425" @default.
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