Finding minimal rare itemsets in a depth-first manner
Abstract
Rare itemsets are an important sort of patterns that have a wide range of practical applications. Although mining rare patterns poses specific algorithmic problems, it is yet insufficiently studied. In a previous work, we proposed a levelwise approach for rare itemset mining. Here, we examine the benefits of depth-first methods for that task as such methods are known to outperform the levelwise ones in many practical cases.