Integrating Bayesian Networks and Simpson’s Paradox in Data Mining

Abstract

This paper proposes to integrate two very different kinds of methods for data mining, namely the construction of Bayesian networks from data and the detection of occurrences of Simpson’s paradox. The former aims at discovering potentially causal knowledge in the data, whilst the latter aims at detecting surprising patterns in the data. By integrating these… (More)

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@inproceedings{Freitas2006IntegratingBN, title={Integrating Bayesian Networks and Simpson’s Paradox in Data Mining}, author={Alex Alves Freitas and Ken McGarry and Elon Correa}, year={2006} }