An Extended Neural Gas Model for Efficient Data Mining Tasks

Jean-Charles Lamirel, Shadi Al Shehabi

This paper presents a numerical association rule extraction method that is based on original quality measures which evaluate to what extent a numerical classification model behaves as a natural symbolic classifier such as a Galois lattice. The proposed method copes with the usual problems of the symbolic association rule extraction method that are computation time and rule selection.

Subjects: Neural Networks; 12. Machine Learning and Discovery

Submitted: Feb 15, 2007

This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.