Sciweavers

160 search results - page 3 / 32
» Analyzing microarray data using quantitative association rul...
Sort
View
IEAAIE
2005
Springer
15 years 3 months ago
Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization
Association rules discovery is a fundamental task in spatial data mining where data are naturally described at multiple levels of granularity. ARES is a spatial data mining system ...
Annalisa Appice, Paolo Buono
BMCBI
2006
109views more  BMCBI 2006»
14 years 9 months ago
Integrated analysis of gene expression by association rules discovery
Background: Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditi...
Pedro Carmona-Saez, Monica Chagoyen, Andrés...
ICPR
2006
IEEE
15 years 10 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
KAIS
2008
119views more  KAIS 2008»
14 years 9 months ago
An information-theoretic approach to quantitative association rule mining
Abstract. Quantitative Association Rule (QAR) mining has been recognized an influential research problem over the last decade due to the popularity of quantitative databases and th...
Yiping Ke, James Cheng, Wilfred Ng
APWEB
2005
Springer
15 years 3 months ago
Mining Quantitative Associations in Large Database
Association Rule Mining algorithms operate on a data matrix to derive association rule, discarding the quantities of the items, which contains valuable information. In order to mak...
Chenyong Hu, Yongji Wang, Benyu Zhang, Qiang Yang,...