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Title: MPGN – An Approach for Discovering Class Association Rules
Authors: Mitov, Iliya
Keywords: Data Mining
Associative Classifiers
Multidimensional Numbered Information Spaces
ArM 32
Issue Date: 2011
Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Citation: Serdica Journal of Computing, Vol. 5, No 4, (2011), 385p-414p
Abstract: The article briefly presents some results achieved within the PhD project R1876Intelligent Systems’ Memory Structuring Using Multidimensional Numbered Information Spaces, successfully defended at Hasselt University. The main goal of this article is to show the possibilities of using multidimensional numbered information spaces in data mining processes on the example of the implementation of one associative classifier, called MPGN (Multilayer Pyramidal Growing Networks).
Description: his article presents some of the results of the Ph.D. thesis Class Association Rule Mining Using MultiDimensional Numbered Information Spaces by Iliya Mitov (Institute of Mathematics and Informatics, BAS), successfully defended at Hasselt University, Faculty of Science on 15 November 2011 in Belgium
ISSN: 1312-6555
Appears in Collections:Volume 5 Number 4

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