A performance analysis of association rule mining algorithms
In this paper, we evaluate the performance of association rule mining algorithms in-terms of execution times and memory usage using the CPU profiler of Java VisualVM. Mainly, and according to a previous work, we studied the performance of two main association rules algorithms which exhibits best res...
| Main Authors: | Fageeri, S.O., Ahmad, R., Alhussian, H. |
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| Format: | Conference or Workshop Item |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.30458 / |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2016
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010469525&doi=10.1109%2fICCOINS.2016.7783236&partnerID=40&md5=536462040637bd613213cc43ea6d1458 http://eprints.utp.edu.my/30458/ |
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| Summary: |
In this paper, we evaluate the performance of association rule mining algorithms in-terms of execution times and memory usage using the CPU profiler of Java VisualVM. Mainly, and according to a previous work, we studied the performance of two main association rules algorithms which exhibits best results interms of execution time and memory usage: Binary-Based algorithm, and Eclat algorithm. The results of the CPU profiler of Java VisualVM showed that Binary-Based algorithm performs better than Eclat algorithm in-terms of both execution times and memory usage. In fact the results showed that Eclat algorithm sometimes even fails to produce any results and reports running out of memory exceptions. © 2016 IEEE. |
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