Analysis of monotonicity properties of some rule interestingness measures
Salvatore Greco, Roman Słowiński, Izabela Szczęch · Control and Cybernetics · 2009
One of the crucial problems in the field of know- ledge discovery is development of good interestingness measures for evaluation of the discovered patterns. In this paper, we consider quantitative, objective interestingness measures for if..., then... association rules. We focus on three popular interestingness mea- sures, namely rule interest function of Piatetsky-Shapiro, gain mea- sure of Fukuda et al., and dependency factor used by Pawlak. We verify whether they satisfy the valuable property M of monotonic de- pendency on the number of objects satisfying or not the premise or the conclusion of a rule, and property of hypothesis symmetry (HS). Moreover, analytically and through experiments we show an inter- esting relationship between those measures and two other commonly used measures of rule support and anti-support.