Considering Causality In Data Mining

Data mining holds the promise of extracting unsuspected information from very large databases. Methods have been developed to build association rules from large data sets. Association rules indicate the strength of association of two or more data attributes. In many ways, the interest in association rules is that they offer the promise (or illusion) of causal, or at least, predictive relationships. Whether it can be said that any association rules express a causal relationship needs to be examined. Causality occupies a position of centrality in human reasoning. In particular, it plays an essential role in human decision-making by providing a basis for choosing that action which is likely to lead to a desired result. Key-Words:causality, data mining, association rules * Parts of this work were performed while the author was a visiting at BISC, Computer Science Division, EECS Department, University of California, Berkeley