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» Classification with reject option in gene expression data
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BMCBI
2006
198views more  BMCBI 2006»
14 years 9 months ago
Gene selection and classification of microarray data using random forest
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
Ramón Díaz-Uriarte, Sara Alvarez de ...
ADMA
2006
Springer
131views Data Mining» more  ADMA 2006»
15 years 3 months ago
Distance Guided Classification with Gene Expression Programming
Gene Expression Programming (GEP) aims at discovering essential rules hidden in observed data and expressing them mathematically. GEP has been proved to be a powerful tool for cons...
Lei Duan, Changjie Tang, Tianqing Zhang, Dagang We...
109
Voted
ACIIDS
2010
IEEE
170views Database» more  ACIIDS 2010»
14 years 7 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
ISMB
2000
14 years 10 months ago
Analysis of Gene Expression Microarrays for Phenotype Classification
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
Andrea Califano, Gustavo Stolovitzky, Yuhai Tu
76
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ICMLA
2008
14 years 11 months ago
Microarray Classification from Several Two-Gene Expression Comparisons
We describe our contribution to the ICMLA2008 "Automated Micro-Array Classification Challenge". The design of our classifier is motivated by the special scenario encounte...
Donald Geman, Bahman Afsari, Aik Choon Tan, Daniel...