MPGN – An Approach for Discovering Class Association Rules


Autoria(s): Mitov, Iliya
Data(s)

04/04/2012

04/04/2012

2011

Resumo

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

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).

Identificador

Serdica Journal of Computing, Vol. 5, No 4, (2011), 385p-414p

1312-6555

http://hdl.handle.net/10525/1635

Idioma(s)

en

Publicador

Institute of Mathematics and Informatics Bulgarian Academy of Sciences

Palavras-Chave #Data Mining #Classification #Associative Classifiers #MPGN #Multidimensional Numbered Information Spaces #ArM 32
Tipo

Article