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Customers who
buy beer and sausage
also tend to buy hamburger
with {confidence = 0.7}
in
{
support = 0.15
}
Customers who
buy strawberries
also tend to buy whipped cream
with {confidence = 0.8}
in {support = 0.2}
Fig. 3. Association rules
At first glance, conditional and association rules seem to imply a causal
or cause-effect relationship. That is:
A customer's purchase of both sausage and beer causes the customer
to also buy hamburger.
Unfortunately, all that is discovered is the existence of a statistical relationship
between the items. They have a degree of joint occurrence. The nature of the
relationship is not identified. Not known is whether the presence of an item
or sets of items causes the presence of another item or set of items; or the
converse, or some other phenomenon causes them to occur together.
Purely accidental relationships do not have the same decision value, as do
causal relationships. For example,
IF it is true that buying both beer and sausage somehow causes
someone to buy beer ,
THEN: A merchant might profitably put beer (or the likewise
associated sausage )onsale
AND at the same time: Increase the price of hamburger to com-
pensate for the sausages' reduce sale price.
On the other hand, knowing that
Bread and milk are often purchased in the same store visit
may not be as useful decision making information as both products are com-
monly purchased on every store visit. A knowledge of frequent co-occurrences
of bread and milk purchases might lead us to placing the bread and milk at
opposite ends of the store to force shoppers to visit more of the store and
consequently make more impulse buying decisions. However, there is a limit
to how often when such a physical distance distribution can be reasonably
effected. What is most valuable is knowledge of true causal relationships.
Tangentially, what might be of interest is discovering if there is a causal
relationship between the purchase of bananas and something else. (It turns out
that bananas are the most frequently purchased food item at Wal-Mart [20]).
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