Association Rules Optimization using Particle Swarm Optimization Algor - Mishra, Manuj;Pathak, Ram
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In data mining, Association rule mining is one of the popular and simple method to find the frequent item sets from a large data set. While generating frequent item sets from a large data set using association rule mining, computer takes too much time. This can be improved by using artificial bee colony algorithm (ABC). The Artificial bee colony algorithm is an optimization algorithm based on the foraging behavior of artificial honey bees. In this paper, artificial bee colony algorithm is used to generate high quality association rules for finding frequent item sets from large data sets.

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Produktbeschreibung
In data mining, Association rule mining is one of the popular and simple method to find the frequent item sets from a large data set. While generating frequent item sets from a large data set using association rule mining, computer takes too much time. This can be improved by using artificial bee colony algorithm (ABC). The Artificial bee colony algorithm is an optimization algorithm based on the foraging behavior of artificial honey bees. In this paper, artificial bee colony algorithm is used to generate high quality association rules for finding frequent item sets from large data sets.
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Autorenporträt
Manuj Mishra is an Assistant professor, department of computer science & engineering, in institute of technology & management(ITM)Gwalior. He has published research paper in IEEE conference.