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Creation of Approximate Rules based on Posterior Probability
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 Title & Authors
Creation of Approximate Rules based on Posterior Probability
Park, In-Kyu; Choi, Gyoo-Seok;
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 Abstract
In this paper the patterns of information system is reduced so that control rules can guarantee fast response of queries in database. Generally an information system includes many kinds of necessary and unnecessary attribute. In particular, inconsistent information system is less likely to acquire the accuracy of response. Hence we are interested in the simple and understandable rules that can represent useful patterns by means of rough entropy and Bayesian posterior probability. We propose an algorithm which can reduce control rules to a minimum without inadequate patterns such that the implication between condition attributes and decision attributes is measured through the framework of rough entropy. Subsequently the validation of the proposed algorithm is showed through test information system of new employees appointment.
 Keywords
Data Mining;Cluster Analysis;Uncertainty;Entropy;Rough Set;
 Language
Korean
 Cited by
 References
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