Bonfring International Journal of Data Mining
Online ISSN: 2277-5048 | Print ISSN: 2250-107X | Frequency: 4 Issues/Year
Impact Factor: 0.245 | International Scientific Indexing(ISI) calculate based on International Citation Report(ICR)
RST Approach for Efficient CARs Mining
Abstract:
In data mining, an association rule is a pattern that states the occurrence of two items (premises and consequences) together with certain probability. A class association rule set (CARs) is a subset of association rules with classes specified as their consequences. This paper focuses on class association rules mining based on the approach of Rough Set Theory (RST). In addition, this paper presents an algorithm for finest class rule set mining inspired from Apriori algorithm, where the support and confidence are computed based on the elementary set of lower approximation inspired from RST. The proposed approach has been shown very effective, where the rough set approach for class association discovery is much simpler than the classic association method
Keywords: Data Mining, Rough Set Theory, Class Association Rule, Association Rule mining, NAR, Bitmap, Class Association Rules
Volume: 4 | Issue: 4
Pages: 34-40
Issue Date: November , 2014
DOI: 10.9756/BIJDM.10365
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