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Thabtah, Fadi Abdeljaber, Mahmood, Qazafi and McCluskey, T.L. (2008) Looking at the Class Associative Classification Training Algorithm. Fifth International Conference on Information Technology: New Generations, 2008. ITNG 2008.. pp. 426-431.
Metadata only available from this repository.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
| Item Type: | Article |
|---|---|
| Subjects: | T Technology > T Technology (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Schools: | School of Computing and Engineering School of Computing and Engineering > Pedagogical Research Group School of Computing and Engineering > Informatics Research Group School of Computing and Engineering > Informatics Research Group > Knowledge Engineering and Intelligent Interfaces |
| Related URLs: | |
| Depositing User: | Briony Heyhoe |
| Date Deposited: | 27 Jan 2009 11:22 |
| Last Modified: | 20 Jul 2011 10:13 |
| URI: | http://eprints.hud.ac.uk/id/eprint/3216 |
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