Question

1. Describe the 2-step process of association mining

2. Describe how the Apriori principle is used in the step of rule generate

Answer 1

1Ans: Association Mining is used for finding the strong association rules and reduces time complexity by using thresholds.

It is a two-step process:

1. Find all Frequent Item sets that are having support value greater than or equal to the threshold(i.e min. support value).
2. Generating Strong Association Rules from the frequent item sets .

• For every frequent item set F, find all non-empty subsets of F. For every such subset A, if the ratio of support(F) to support(A) is greater than or equal to minimum confidence then it has strong association.
• The Overall Performance of mining association rules is determined by first step itself.

2Ans: Apriori is an algorithm which determines frequent itemset. Apriori principle is used in the step of rule generate for generating association rules from a given data set. Apriori Algorithm uses an iterative approach known as "level-wise" search for determining frequent itemsets.

NOTE: Apriori Property States that, "any subset of large itemset must be large". and it is "anti-monotone" (i.e if a set cannot pass a test, all of it's super sets will fail the same test as well)