MPGN – An Approach for Discovering Class Association Rules

Mitov, Iliya. "MPGN – An Approach for Discovering Class Association Rules." Serdica Journal of Computing 5.4 (2011): 385-414. <http://eudml.org/doc/219516>.

@article{Mitov2011,
abstract = {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 BelgiumThe 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).},
author = {Mitov, Iliya},
journal = {Serdica Journal of Computing},
keywords = {Data Mining; Classification; Associative Classifiers; MPGN; Multidimensional Numbered Information Spaces; ArM 32},
language = {eng},
number = {4},
pages = {385-414},
publisher = {Institute of Mathematics and Informatics Bulgarian Academy of Sciences},
title = {MPGN – An Approach for Discovering Class Association Rules},
url = {http://eudml.org/doc/219516},
volume = {5},
year = {2011},
}

TY - JOUR
AU - Mitov, Iliya
TI - MPGN – An Approach for Discovering Class Association Rules
JO - Serdica Journal of Computing
PY - 2011
PB - Institute of Mathematics and Informatics Bulgarian Academy of Sciences
VL - 5
IS - 4
SP - 385
EP - 414
AB - 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 BelgiumThe 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).
LA - eng
KW - Data Mining; Classification; Associative Classifiers; MPGN; Multidimensional Numbered Information Spaces; ArM 32
UR - http://eudml.org/doc/219516
ER -