Process
Association rules are usually required to satisfy a user-specified minimum support and a user-specified minimum confidence at the same time. Association rule generation is usually split up into two separate steps:
- First, minimum support is applied to find all frequent itemsets in a database.
- Second, these frequent itemsets and the minimum confidence constraint are used to form rules.
While the second step is straightforward, the first step needs more attention.
Finding all frequent itemsets in a database is difficult since it involves searching all possible itemsets (item combinations). The set of possible itemsets is the power set over and has size (excluding the empty set which is not a valid itemset). Although the size of the powerset grows exponentially in the number of items in, efficient search is possible using the downward-closure property of support (also called anti-monotonicity) which guarantees that for a frequent itemset, all its subsets are also frequent and thus for an infrequent itemset, all its supersets must also be infrequent. Exploiting this property, efficient algorithms (e.g., Apriori and Eclat) can find all frequent itemsets.
Read more about this topic: Association Rule Learning
Famous quotes containing the word process:
“When you start with a portrait and search for a pure form, a clear volume, through successive eliminations, you arrive inevitably at the egg. Likewise, starting with the egg and following the same process in reverse, one finishes with the portrait.”
—Pablo Picasso (1881–1973)
“The process of education in the oldest profession in the world is like any other educational process, in that it requires time and effort and patience; it can only be acquired by taking one step at a time, though the steps become accelerated after the first few.”
—Madeleine [Blair], U.S. prostitute and “madam.” Madeleine, ch. 4 (1919)
“A man had better starve at once than lose his innocence in the process of getting his bread.”
—Henry David Thoreau (1817–1862)