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» Mining Default Rules from Statistical Data
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FLAIRS
2009
13 years 9 months ago
Mining Default Rules from Statistical Data
In this paper, we are interested in the qualitative knowledge that underlies some given probabilistic information. To represent such qualitative structures, we use ordinal conditi...
Gabriele Kern-Isberner, Matthias Thimm, Marc Finth...
PAKDD
1999
ACM
113views Data Mining» more  PAKDD 1999»
14 years 3 months ago
Characterization of Default Knowledge in Ripple Down Rules Method
Abstract. \Ripple Down Rules (RDR)" Method is one of the promising approaches to directly acquire and encode knowledge from human experts. It requires data to be supplied incr...
Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda, Tak...
KES
2004
Springer
14 years 4 months ago
A Comparison of Two Approaches to Data Mining from Imbalanced Data
Our objective is a comparison of two data mining approaches to dealing with imbalanced data sets. The first approach is based on saving the original rule set, induced by the LEM2 ...
Jerzy W. Grzymala-Busse, Jerzy Stefanowski, Szymon...
JIPS
2008
116views more  JIPS 2008»
13 years 11 months ago
An Empirical Study of Qualities of Association Rules from a Statistical View Point
: Minimum support and confidence have been used as criteria for generating association rules in all association rule mining algorithms. These criteria have their natural appeals, s...
Maryann Dorn, Wen-Chi Hou, Dunren Che, Zhewei Jian...
CEC
2008
IEEE
14 years 5 months ago
Distributed multi-relational data mining based on genetic algorithm
—An efficient algorithm for mining important association rule from multi-relational database using distributed mining ideas. Most existing data mining approaches look for rules i...
Wenxiang Dou, Jinglu Hu, Kotaro Hirasawa, Gengfeng...