| SMART JOURNAL OF BUSINESS MANAGEMENT STUDIES |
VOL. 5 |
NO. 2 |
PAPER 3 |
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PERFORMANCE ANALYSIS ON ASSOCIATION RULE IN DATA MINING |
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| T. Muthukumar* and M. Ramasamy** |
* Research Scholar, Sathyabama University, Chennai, Tamil Nadu, India. (Assistant Director-Board of Studies –
The Institute of Chartered Accountants of India – New Delhi) |
| ** Dean, PG Studies, Madha Engineering College, Chennai, Tamil Nadu, India |
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| One of the most important problems in data mining is to find association rules. The association rule mining can be classified into two main
categories: the level-wise algorithms and the tree based algorithms. The
level-wise algorithm like Apriori, scan the entire database multiple
times and also generate a huge number of candidate sets. It also needs
to repeatedly scan the database and check a large set of candidates by
pattern matching, Tree based algorithms, like FP-tree, scan the database
only twice. Another tree based algorithm, P-Tree is constructed by a
single scan of a database and it updates the Ptree by one scan of new
data. The performance study shows that in majority of cases, Pattern
Tree achieves better performance and efficiency than Apriori and FP
algorithms. |
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