Bakar, W.A.W.A. and Saman, M.D.M. and Abdullah, Z. and Jalil, M.A. and Herawan, T. (2016) Mining dense data: Association rule discovery on benchmark case study. Jurnal Teknologi, 78 (2-2). pp. 131-135. ISSN 0127-9696,
Full text not available from this repository.Abstract
Data Mining (DM), is the process of discovering knowledge and previously unknown pattern from large amount of data. The association rule mining has been in trend where a new pattern analysis can be discovered to project for an important prediction about any issues. In this article, we present comparison result between Apriori and FP-Growth algorithm in generating association rules based on a benchmark data from frequent itemset mining data repository. Experimentation with the two (2) algorithms are done in Rapid Miner 5.3.007 and the performance result is shown as a comparison. The results obtained confirmed and verified the results from the previous works done.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Data Mining (DM); Association Rule Mining (ARM); Rapid Miner (RM); Frequent itemset; Interestingness measure |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 06 Oct 2017 06:48 |
| Last Modified: | 06 Oct 2017 06:48 |
| URI: | http://eprints.um.edu.my/id/eprint/17907 |
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