Mining Classification Rules without Support: an Anti-monotone Property of Jaccard Measure

摘要

We propose a general definition of anti-monotony, and study the anti-monotone property of the Jaccard measure for classification rules. The discovered property can be inserted in an APRIORI-like algorithm and can prune the search space without any support constraint. Moreover, the algorithm is complete since, it outputs all interesting rules with respect to the measure of Jaccard. The proposed pruning strategy can then be used to efficiently find nuggets of knowledge.