Comparative Study of Revised FP - Growth, Weighted Apriori and Fuzzy Apriori Algorithm

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Provided by: International Journal of Engineering Trends and Technology
Topic: Data Management
Format: PDF
Association rule mining is considered as one of the crucial step in finding the frequent itemsets, for the purpose of extracting association rules from high voluminous relational databases. Many algorithms were developed to find the frequently occurred Itemsets. The association rules were considered as better, since they are useful at the level of decision making. The main benefit of the Apriori-algorithm is that it doesn't need to generate conditional patterns iteratively and adds the pruning step to eliminate the irrelevant data. FP-tree is highly a compact representation of all relevant frequency information in the data set.
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