Comparing rule measures for predictive association rules

Abstract

We study the predictive ability of some association rule measures typically used to assess descriptive interest. Such measures, namely conviction, lift and χ2 are compared with confidence, Laplace, mutual information, cosine, Jaccard and φ-coefficient. As prediction models, we use sets of association rules. Classification is done by selecting the best rule, or by weighted voting. We performed an evaluation on 17 datasets with different characteristics and conclude that conviction is on average the best predictive measure to use in this setting. We also provide some meta-analysis insights for explaining the results. © Springer-Verlag Berlin Heidelberg 2007.