An Exhaustive Covering Approach to Parameter-Free Mining of Non-redundant Discriminative Itemsets
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چکیده
منابع مشابه
A lattice-based approach for mining most generalization association rules
Traditional association rules consist of some redundant information. Some variants based on support and confidence measures such as non-redundant rules and minimal non-redundant rules were thus proposed to reduce the redundant information. In the past, we proposed most generalization association rules (MGARs), which were more compact than (minimal) non-redundant rules in that they considered th...
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In general frequent itemsets are generated from large data sets by applying various association rule mining algorithms, these produce many redundant frequent itemsets. In this paper we proposed a new framework for Non-redundant frequent itemset generation using closed frequent itemsets without lose of information on Taxonomy Datasets using concept lattices. General Terms Frequent Pattern, Assoc...
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There are many algorithms developed for improvement the time of mining frequent itemsets (FI) or frequent closed itemsets (FCI). However, the algorithms which deal with the time of generating association rules were not put in deep research. In reality, in case of a database containing many FI/FCI (from ten thousands up to millions), the time of generating association rules is much larger than t...
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