INFORMATION ANALYSIS WITH APRIORI ALGORITHM USING REGULATION ASSOCIATION MINING

Praveen, Dr, Mohan Rao
2018 Indian J.Sci.Res   unpublished
Presently Data mining has a more of e-Commerce applications. The key problem is how to find useful concealed patterns for better business applications in the retail sector. For the solution of these problems, The Apriori algorithm is one of the most popular data mining approaches for finding frequent item sets from a transaction dataset and derives association rules. Rules are the discovered knowledge from the data base. Finding frequent item set (item sets with frequency larger than or equal
more » ... ger than or equal to a user specified minimum support) is not small because of its combinatorial explosion. Once frequent item sets are obtained, it is straightforward to generate association rules with confidence larger than or equal to a user specified minimum confidence. The paper illustrating apriori algorithm on simulated database and finds the association rules on different confidence value.
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