An effective algorithm for mining interesting quantitative association rules

摘要: In this paper, we describe a novel technique, called APACS2, for mining interesting quantitative association rules from very large databases. To effectively mine such rules, APACS2 employs adjusted difference analysis. The use of technique has the advantage that it does not require any user-supplied thresholds which are often hard to determine. Furthermore, also allows users discover both positive and negative rules. A rule tells us record having certain attribute value will have another whereas value. fact is able uses an objective yet meaningful measure determine interestingness makes effective at different data tasks.