NDLI: Multi-relational Bayesian Classification Algorithm with Rough Set

Content Provider	IEEE Xplore Digital Library
Author	Chunying Zhang Jing Wang
Copyright Year	2010
Description	Author affiliation: College of Science, Hebei Polytechnic University, Tangshan Hebei, China (Chunying Zhang; Jing Wang)
Abstract	A Multi-relational Bayesian Classification Algorithm with Rough Set is proposed in this paper. The concept of relational graph used to dynamic choice associative table associated with the target table, and a tuple ID propagation approach is used to solve directly the association rule mining problem with multiple database relations, and the concept of Core in Rough Set is introduced, simplify the associative table. Compared with the traditional algorithm,it improves the accuracy rate. Experimental results show that its running rate is much higher than that of Bayesian Classification Algorithm and Graph_NB Algorithm.
Starting Page	1565
Ending Page	1568
File Size	209201
Page Count	4
File Format	PDF
ISBN	9781424459315
e-ISBN	9781424459346
DOI	10.1109/FSKD.2010.5569347
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Multi-relational Classification Accuracy relational graph Bayesian methods Heuristic algorithms Class label propagation Relational databases Classification algorithms associative table Core
Content Type	Text
Resource Type	Article

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Multi-relational Bayesian Classification Algorithm with Rough Set