Ansaf Salleb and Teddy Turmeaux and Christel Vrain and Cyril Nortet Mining Quantitative Association Rules in a Atherosclerosis Dataset , PKDD Discovery Challenge 2004 (co-located with the 6th European Conference on Principles and Practice of Knowledge Discovery in Databases) , 98--103 , sep , 2004 Abstract Mining association rules in databases has become a popular task in data mining. However, most research has focused on categorical attributes in relational table whereas in practice, this table contains also numeric attributes. In this paper, we propose to experiment QuantMiner, a genetic-based algorithm software for mining quantitative association rules on a atherosclerosis dataset. We give some experimental results obtained in both the description and the characterization of this disease. Keywords : data mining, association rule, numeric attribute, discretization, categorical attribute, description, discrimination, evolutionary algorithm. This web site is maintained by René Quiniou using the Weave system from the Caravel project: http://www-caravel.inria.fr. Last modification: 10-07-2011 09:54:25