Abstract
Associative classification (AC) is a branch in data mining that utilises association rule discovery methods in classification problems. In this paper, we propose a new training method called Looking at the Class (LC), which can be adapted by any rule-based AC algorithm. Unlike the traditional Classification based on Association rule (CBA) training method, which joins disjoint itemsets regardless of their class labels, our method joins only itemsets with similar class labels during the training phase. This prevents the accumulation of too many unnecessary merging during learning, and consequently results in huge saving (58%-91%) with reference of computational time and memory on large datasets.
Original language | English |
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Title of host publication | Proceedings of the Fifth International Conference on Information Technology |
Subtitle of host publication | New Generations - ITNG 2008 |
Editors | Shahram Latifi |
Publisher | IEEE |
Pages | 426-431 |
Number of pages | 6 |
ISBN (Print) | 0769530990, 9780769530994 |
DOIs | |
Publication status | Published - 18 Apr 2008 |
Event | International Conference on Information Technology: New Generations - Las Vegas, United States Duration: 7 Apr 2008 → 9 Apr 2008 http://www.itng.info/OLD/2008Web/ |
Conference
Conference | International Conference on Information Technology |
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Abbreviated title | ITNG 2008 |
Country/Territory | United States |
City | Las Vegas |
Period | 7/04/08 → 9/04/08 |
Internet address |