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Determination of frequent sets from a large database is the key to Association Rule mining from the point view of efficiency of algorithms to scale up and discovering frequent sets which lead to useful association rules. Some of the existing methods have either very low or very high pruning, which is the cause of generation of larger or lesser number of(More)
Useful rule formation from frequent itemsets in a large database is a crucial task in Association Rule mining. Traditionally association rules refer to associations between two frequent sets and measured by their confidence. This approach basically concentrates on positive associations and thereby do not study the effect of dissociation and null(More)
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