Protein Classification Using N-gram Technique and Association Rules

2. State Of The Art

The extraction of association rules, is an important task, seem particularly well-adapted, to discover the relations between the sets of elements from a database; In its most common version, an association rule is characterized as follows: I= {i1, i2, ..., im} Set of items, and T = {t1, t2, ..., tn} set of transactions, each one associated with a subset of I. An association rule is defined by X → Y, in which X, Y ⊆ I and X∩Y = ∅, each rule induces two notions, the support and the confidence, measure respectively the scope and the precision of the rule.

For example, rule AB → C, support = 20%, and confidence = 80% indicates that when A and B occur, C also occurs in 80% of cases, and all three events occurs at the same time in 20% of all instances. The user sets a minimum support threshold and a minimum confidence threshold for the generation of rules.