Discovering causality in large databases

摘要

A causal rule between two variables, X→Y, captures the relationship that the presence of X causes the appearance of Y. Because of its usefulness (compared to association rules), techniques for mining causal rules are beginning to be developed. However, the effectiveness of existing methods (such as the LCD and CU-path algorithms) are limited to mining causal rules among simple variables, and are inadequate to discover and represent causal rules among multi-value variables. In this paper, we propose that he causality between variables X and Y be represented in the form X→Y with conditional probability matrix M_Y/X.