A Fuzzy Rule Mining Approach involving Absent Items

Abstract

In this paper we present how to extract fuzzy association rules involving both the presence and the absence of items using a fuzzy rule mining procedure introduced by the authors in previous works. The rule mining procedure is based on the GUHA logical model, fuzzified via a recently proposed representation of gradualness. We present some results obtained with real datasets.