Final answer:
The Rescorla-Wagner (RW) model, rooted in psychology, cannot explain the business-oriented rules of association such as Rule of Support, Rule of Confidence, Rule of Lift, and Rule of Conviction, which are used in data mining.
Step-by-step explanation:
The four rules of association mentioned - Rule of Support, Rule of Confidence, Rule of Lift, and Rule of Conviction - are all associated with market basket analysis in data mining, where they are used to find interesting relationships among items in large datasets. However, when we consider the Rescorla-Wagner (RW) model, which is a psychological model of associative learning, it cannot be employed to explain these business-oriented rules of association. The RW model explains how the strength of a stimulus-response association is learned and how it changes over time through conditioning - a process that is distinctly different from the computation of association rules in a dataset. In essence, the RW model pertains to learning associations based on stimulus and response in the field of psychology, whereas the rules of association pertain to the patterns of item relationships in datasets analyzed within the context of business and technology.