Mining dense data: Association rule discovery on benchmark case study
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 compar...
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| Format: | Article |
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Penerbit UTM Press
2016
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| _version_ | 1796947241178497024 |
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| author | Bakar, W.A.W.A. Saman, M.D.M. Abdullah, Z. Jalil, M.A. Herawan, T. |
| author_facet | Bakar, W.A.W.A. Saman, M.D.M. Abdullah, Z. Jalil, M.A. Herawan, T. |
| author_sort | Bakar, W.A.W.A. |
| collection | UM |
| description | 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. |
| first_indexed | 2024-03-06T05:43:52Z |
| format | Article |
| id | um.eprints-17907 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:43:52Z |
| publishDate | 2016 |
| publisher | Penerbit UTM Press |
| record_format | dspace |
| spelling | um.eprints-179072017-10-06T06:48:35Z http://eprints.um.edu.my/17907/ Mining dense data: Association rule discovery on benchmark case study Bakar, W.A.W.A. Saman, M.D.M. Abdullah, Z. Jalil, M.A. Herawan, T. QA75 Electronic computers. Computer science 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. Penerbit UTM Press 2016 Article PeerReviewed 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, |
| spellingShingle | QA75 Electronic computers. Computer science Bakar, W.A.W.A. Saman, M.D.M. Abdullah, Z. Jalil, M.A. Herawan, T. Mining dense data: Association rule discovery on benchmark case study |
| title | Mining dense data: Association rule discovery on benchmark case study |
| title_full | Mining dense data: Association rule discovery on benchmark case study |
| title_fullStr | Mining dense data: Association rule discovery on benchmark case study |
| title_full_unstemmed | Mining dense data: Association rule discovery on benchmark case study |
| title_short | Mining dense data: Association rule discovery on benchmark case study |
| title_sort | mining dense data association rule discovery on benchmark case study |
| topic | QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT bakarwawa miningdensedataassociationrulediscoveryonbenchmarkcasestudy AT samanmdm miningdensedataassociationrulediscoveryonbenchmarkcasestudy AT abdullahz miningdensedataassociationrulediscoveryonbenchmarkcasestudy AT jalilma miningdensedataassociationrulediscoveryonbenchmarkcasestudy AT herawant miningdensedataassociationrulediscoveryonbenchmarkcasestudy |