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An immunological algorithm for discovering small-disjunct rules in data mining

In essence, small disjuncts are rules covering a small number of examples. Although each small disjunct covers a small number of examples, the set of all small disjuncts can collectively cover a large number of examples. Indeed, this work presents evidence that this is the case. This work also proposes a hybrid decision tree/immunological algorithm method to cope with the problem of small disjuncts. The basic idea is that examples belonging to large disjuncts are classified by rules produced by a decision-tree algorithm, while examples belonging to small disjuncts are classified by an immunological algorithm, specifically designed for this task.