Abstract
Partial association test is a statistical means to test whether the association between two variables is persistent given other variables. The CR-PA algorithm has been developed to identify causal rules (CRs) by integrating association rule mining and partial association (PA) tests. The use of association rule mining enables fast identification of causal hypotheses (association rules) from large data sets, and partial association tests on these association rules eliminate non-persistent associations. This chapter firstly describes the basics of partial association tests and association rule mining, and then the CR-PA algorithm is presented in detail, followed by the discussions on the complexity and false discoveries of the algorithm. A tool which implements CR-PA is also introduced.
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Li, J., Liu, L., Le, T. (2015). Causal Rule Discovery with Partial Association Test. In: Practical Approaches to Causal Relationship Exploration. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-14433-7_4
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DOI: https://doi.org/10.1007/978-3-319-14433-7_4
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