Improving the Quality of Association Rule Mining by Means of Rough Sets
Daniel Delić, Hans‐J. Lenz, Mattis Neiling · Advances in intelligent and soft computing · 2002
We evaluate the rough set and the association rule method with respect to their performance and the quality of the produced rules. It is shown that despite their different approaches, both methods are based on the same principle and, consequently, must generate identical rules. However, they differ strongly with respect to performance Subsequently an optimized association rule procedure is presented which unifies the advantages of both methods.