Performance Evaluation of Classification-Based Association Rule Mining for Knowledge Discovery

Minakshi Kalra

Abstract


Association rule mining is used to find the interesting association or correlation relationships among a large set of data items. This paper proposes classification-based association rule mining (CBA). Besides this, the performance of Apriori algorithm is also analyzed on five UCI machine learning datasets. Weka tool is used to analyze the performance of Apriori algorithm. The classification based on Apriori is compared with the existing classification techniques. The proposed classification algorithm exhibits superiority over the existing classification algorithms.


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References


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http://www.ics.uci.edu/_mlearn/MLRepository.html.


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