Geodesic
MPGN – An Approach for Discovering Class Association Rules
Serdica Journal of Computing, Tome 5 (2011) no. 4, pp. 385-414.

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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).
Keywords: Data Mining, Classification, Associative Classifiers, MPGN, Multidimensional Numbered Information Spaces, ArM 32 
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Mitov, Iliya. MPGN – An Approach for Discovering Class Association Rules. Serdica Journal of Computing, Tome 5 (2011) no. 4, pp. 385-414. http://geodesic.mathdoc.fr/item/SJC_2011_5_4_a5/