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» Mining Optimized Association Rules for Numeric Attributes
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CEC
2008
IEEE
15 years 4 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...
RSFDGRC
2005
Springer
187views Data Mining» more  RSFDGRC 2005»
15 years 3 months ago
Handling Missing Attribute Values in Preterm Birth Data Sets
The objective of our research was to find the best approach to handle missing attribute values in data sets describing preterm birth provided by the Duke University. Five strategi...
Jerzy W. Grzymala-Busse, Linda K. Goodwin, Witold ...
SDM
2009
SIAM
143views Data Mining» more  SDM 2009»
15 years 7 months ago
Finding Representative Association Rules from Large Rule Collections.
One of the most well-studied problems in data mining is computing association rules from large transactional databases. Often, the rule collections extracted from existing datamin...
Warren L. Davis IV, Peter Schwarz, Evimaria Terzi
PAKDD
2005
ACM
94views Data Mining» more  PAKDD 2005»
15 years 3 months ago
Progressive Sampling for Association Rules Based on Sampling Error Estimation
We explore in this paper a progressive sampling algorithm, called Sampling Error Estimation (SEE), which aims to identify an appropriate sample size for mining association rules. S...
Kun-Ta Chuang, Ming-Syan Chen, Wen-Chieh Yang
ISCC
2002
IEEE
147views Communications» more  ISCC 2002»
15 years 3 months ago
A new method for finding generalized frequent itemsets in generalized association rule mining
Generalized association rule mining is an extension of traditional association rule mining to discover more informative rules, given a taxonomy. In this paper, we describe a forma...
Kritsada Sriphaew, Thanaruk Theeramunkong