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» Redundancy based feature selection for microarray data
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IMSCCS
2007
IEEE
15 years 4 months ago
Asymmetric Bagging and Feature Selection for Activities Prediction of Drug Molecules
Background: Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cy...
Guo-Zheng Li, Hao-Hua Meng, Mary Qu Yang, Jack Y. ...
HIS
2009
14 years 7 months ago
A Swarm-Based Rough Set Approach for Group Decision Support Systems
This paper present a class of investment problem, in which many items could be chosen in a group decision environment. Usually there is a decision table from the board of director...
Mingyan Zhao, Hongbo Liu, Ajith Abraham, Emilio Co...
BMCBI
2006
115views more  BMCBI 2006»
14 years 9 months ago
Multivariate curve resolution of time course microarray data
Background: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), i...
Peter D. Wentzell, Tobias K. Karakach, Sushmita Ro...
BMCBI
2006
173views more  BMCBI 2006»
14 years 9 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
SDM
2008
SIAM
157views Data Mining» more  SDM 2008»
14 years 11 months ago
ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data
Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Suc...
M. Maruf Hossain, Md. Rafiul Hassan, James Bailey