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ACIIDS
2010
IEEE
170views Database» more  ACIIDS 2010»
13 years 2 months ago
On the Effectiveness of Gene Selection for Microarray Classification Methods
Microarray data usually contains a high level of noisy gene data, the noisy gene data include incorrect, noise and irrelevant genes. Before Microarray data classification takes pla...
Zhongwei Zhang, Jiuyong Li, Hong Hu, Hong Zhou
BMCBI
2007
143views more  BMCBI 2007»
13 years 4 months ago
Gene selection for classification of microarray data based on the Bayes error
Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
Ji-Gang Zhang, Hong-Wen Deng
BMCBI
2005
118views more  BMCBI 2005»
13 years 4 months ago
Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes
Background: In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be us...
Thanyaluk Jirapech-Umpai, J. Stuart Aitken
PR
2006
161views more  PR 2006»
13 years 4 months ago
Incremental wrapper-based gene selection from microarray data for cancer classification
Gene expression microarray is a rapidly maturing technology that provides the opportunity to assay the expression levels of thousands or tens of thousands of genes in a single exp...
Roberto Ruiz Sánchez, José Crist&oac...
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
14 years 5 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu