Abstract
Mining association rules and correlation relationships have been studied in the data mining field for many years. However, the rules mined only indicate association relationships among variables in an interested system. They do not specify the essential underlying mechanism of the system that describe causal relationships. In this paper, we present an approach for mining causal relationships among attributes and propose a potential application in the field of bioinformatics. Based on the theory of causal diagram, we show the properties of our approach.
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He, Y.B., Geng, Z., Liang, X. (2005). An Approach to Mining Local Causal Relationships from Databases. In: Li, X., Wang, S., Dong, Z.Y. (eds) Advanced Data Mining and Applications. ADMA 2005. Lecture Notes in Computer Science(), vol 3584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527503_8
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DOI: https://doi.org/10.1007/11527503_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27894-8
Online ISBN: 978-3-540-31877-4
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