计算机科学技术学报(英文版)
計算機科學技術學報(英文版)
계산궤과학기술학보(영문판)
COMPUTER JOURNAL OF SCIENCE AND TECHNOLOGY
2002年
3期
304-313
,共10页
data mining%class association rule%exception class association rule%pruning
In this paper, a new effective method is proposed to find class association rules (CAR), to get useful class association rules (UCAR) by removing the spurious class association rules (SCAR), and to generate exception class association rules (ECAR) for each UCAR. CAR mining, which integrates the techniques of classification and association, is of great interest recently. However, it has two drawbacks: one is that a large part of CARs are spurious and maybe misleading to users; the other is that some important ECARs are difficult to find using traditional data mining techniques. The method introduced in this paper aims to get over these flaws. According to our approach, a user can retrieve correct information from UCARs and know the influence from different conditions by checking corresponding ECARs. Experimental results demonstrate the effectiveness of our proposed approach.
