On the behavior of the generalizations of the intensity of implication : a data-driven comparative study

Benoît Vaillant (1) , Stéphane Lallich (2) , Philippe Lenca (3)

1 IUT Vannes - Institut Universiteire de Technologie de Vannes (UBS - Université de Bretagne Sud)
2 ERIC - Equipe de Recherche en Ingénierie des Connaissances
3 LUSSI - Département Logique des Usages, Sciences sociales et Sciences de l'Information

In this chapter, we present an original and synthetical overview of most of the commonly used association rule statistical interestingness measures introduced in previous works. These measures usually relate the confidence of a rule to an independency reference situation. Others relate it to indetermination, or impose a minimum confidence threshold. We propose a systematic generalization of these measures, taking into account a reference point, chosen by an expert, in order to apprehend the confidence of a rule. This generalization introduces new connections between measures. They lead to the enhancement of some measures. We then propose new parameterized possibilities. The behavior of the parameterized measures is illustrated using classical datasets, and these measures are compared to their original counter-parts. This study highlights the different properties of each of them and discusses the advantages of our proposition.

Mots clés: Statistical interestingness measure; Intensity of implication; Generalized measures

Domaines: Ordinateur et société [cs.CY]

Benoît Vaillant, Stéphane Lallich, Philippe Lenca. On the behavior of the generalizations of the intensity of implication : a data-driven comparative study. Statistical implicative analysis : theory and applications, 127, Springer, pp.421 - 447, 2008, Studies in computational intelligence, 978-3-540-78982-6. ⟨10.1007/978-3-540-78983-3⟩. ⟨hal-01879301⟩