Multi-objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of Workstations
نویسندگان
چکیده
منابع مشابه
Multi-objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of Workstations
This study presents a fast and scalable multi-objective association rule mining technique using genetic algorithm from large database. The objective functions such as confidence factor, comprehensibility and interestingness can be thought of as different objectives of our association rulemining problem and is treated as the basic input to the genetic algorithm. The outcomes of our algorithm are...
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Abstract as a single objective one. Measures like support, confidence and other interestingness criteria which are used for evaluating a rule, can be thought of as different objectives of association rule mining problem. Support count is the number of records, which satisfies all the conditions that exist in the rule. This objective represents the accuracy of the rules extracted from the da...
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Generally association rule mining (ARM) algorithms, like the apriori algorithm, initial produce frequent itemsets and afterward, from the frequent itemsets, the association rules that go beyond the minimum confidence threshold. When the data is in large volume, it takes number of scans to generate frequent items.It is a better idea if all the association rules generated directly without generat...
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Multi-Objective Genetic Algorithm (MOGA) is a new approach for association rule mining in the market-basket type databases. Finding the frequent itemsets is the most resource-consuming phase in association rule mining, and always does some extra comparisons against the whole database. This paper proposes a new algorithm, Cluster-Based MultiObjective Genetic Algorithm (CBMOGA) which optimizes th...
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Association rule mining problems can be considered as a multi-objective problem rather than as a single objective one. Measures like support count, comprehensibility and interestingness, used for evaluating a rule can be thought of as different objectives of association rule mining problem. Support count is the number of records, which satisfies all the conditions present in the rule. This obje...
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ژورنال
عنوان ژورنال: American Journal of Applied Sciences
سال: 2006
ISSN: 1546-9239
DOI: 10.3844/ajassp.2006.2086.2095