Meaningful discretization of continuous features for association rules mining by means of a SOM

The paper presents the problem of the unsupervised dis- cretization of continuous attributes for association rules mining. It shows commonly used techniques for this aim and highlights their principal lim- itations. To overcome such limitations a method based on the use of a SOM is presented and tested over various real world datasets.