Sciweavers

176 search results - page 9 / 36
» Discovering and ranking important rules
Sort
View
KDD
2005
ACM
73views Data Mining» more  KDD 2005»
14 years 10 months ago
Using relational knowledge discovery to prevent securities fraud
We describe an application of relational knowledge discovery to a key regulatory mission of the National Association of Securities Dealers (NASD). NASD is the world's largest...
Özgür Simsek, David Jensen, Henry G. Gol...
JASIS
2000
143views more  JASIS 2000»
13 years 9 months ago
Discovering knowledge from noisy databases using genetic programming
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Man Leung Wong, Kwong-Sak Leung, Jack C. Y. Cheng
APIN
2008
116views more  APIN 2008»
13 years 10 months ago
Updating generalized association rules with evolving taxonomies
Abstract-Mining generalized association rules between items in the presence of taxonomy has been recognized as an important model in data mining. Earlier work on mining generalized...
Ming-Cheng Tseng, Wen-Yang Lin, Rong Jeng
IDA
2002
Springer
13 years 9 months ago
Measuring the accuracy and interest of association rules: A new framework
It has been pointed out that the usual framework to assess association rules, based on support and confidence as measures of importance and accuracy, has several drawbacks. In part...
Fernando Berzal Galiano, Ignacio J. Blanco, Daniel...
BMCBI
2007
207views more  BMCBI 2007»
13 years 10 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...