A transaction database contains ten transactions as shown be

A transaction database contains ten transactions as shown below: Let min_sup = 30% and min_conf = 50% Using FP-growth, find all frequent itemsets that contain item i. Show the steps Find all the strong association rules whose consequent is i Are there any misleading rules in the result of (b)? If yes, identify them and explain why they are misleading.

Solution

An association rule is an implication of the form AB,
where A and B are frequent itemsets in a transaction database and AB=.
The rule AB can be interpreted as “if itemset A occurs in a transaction,
then itemset B will also likely occur in the same transaction”.
By such information, market personnel can place itemsets A and B within close proximity,
which may encourage the sale of these items together and develop discount strategies
based on such association/correlation found in the data.

Item: attribute=value pair or simply value
usually attributes are converted into binary flags for
each value, e.g. product=“d” is written as “d”
Itemset I : a subset of possible items
Example: I = {A,B,E} (order unimportant)
Transaction: (TID, itemset)

Support of an itemset
sup( I ) = no. of transactions t that support
(that is contain) I
In example database:
sup ({A,B,E}) = 2, sup ({B,C}) = 4
Frequent itemset I is one with at least the
minimum support count
sup( I ) >= minsup