Assessing the Quality of Rules with a New Monotonic Interestingness Measure Z

Authors:
Salvatore Greco;Roman Słowiński;Izabela Szczech
Affiliations:
Faculty of Economics, University of Catania, Catania, Italy 95129;Institute of Computing Science, Poznan University of Technology, Poznan, Poland 60-965 and Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland 01-447;Institute of Computing Science, Poznan University of Technology, Poznan, Poland 60-965
Venue:
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Year:
2006

Citing 4
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Abstract

The development of effective interestingness measures that help in interpretation and evaluation of the discovered knowledge is an active research area in data mining and machine learning. In this paper, we consider a new Bayesian confirmation measure for "if..., then..." rules proposed in [4]. We analyze this measure, called Z, with respect to valuable property M of monotonic dependency on the number of objects in the dataset satisfying or not the premise or the conclusion of the rule. The obtained results unveil interesting relationship between Zmeasure and two other simple and commonly used measures of rule support and anti-support, which leads to efficiency gains while searching for the best rules.