Discovery of causality possibilities
Determining casualty has been a tantalizing gaol throughout human history. Proper sacrifices to the gods were thought to bring rewards; failure to make suitable observations were thought to lead to disaster. Today, 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 casual, or at least, predictive relationships. However, association rules only calculate a joint probability; they do not express a casual relationship. If casual relationships could be discovered, it would be very useful. Our goal is to explore casuality in the data mining context.
causality data mining representation