FUNDAMENTALS OF COMPUTER

Detailed explanation-1: -Association Rule Mining can be viewed as a two-step process: Frequent Itemset Generation:-find all itemsets whose support is greater than or equal to the minimum support threshold.

Detailed explanation-2: -Frequent Itemset – An itemset whose support is greater than or equal to minsup threshold.

Detailed explanation-3: -Frequent itemsets are those items whose support is greater than the threshold value or user-specified minimum support. It means if A & B are the frequent itemsets together, then individually A and B should also be the frequent itemset.

Detailed explanation-4: -The frequency of an item set is measured by the support count, which is the number of transactions or records in the dataset that contain the item set. For example, if a dataset contains 100 transactions and the item set milk, bread appears in 20 of those transactions, the support count for milk, bread is 20.

Detailed explanation-5: -Frequent itemsets (Agrawal et al., 1993, 1996) are a form of frequent pattern. Given examples that are sets of items and a minimum frequency, any set of items that occurs at least in the minimum number of examples is a frequent itemset.