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» Gene Expression Classification: Decision Trees vs. SVMs
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FLAIRS
2003
13 years 6 months ago
Gene Expression Classification: Decision Trees vs. SVMs
Xiaojing Yuan, Xiaohui Yuan, Fan Yang, Jing Peng, ...
SDM
2008
SIAM
157views Data Mining» more  SDM 2008»
13 years 6 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
BMCBI
2005
145views more  BMCBI 2005»
13 years 4 months ago
CAGER: classification analysis of gene expression regulation using multiple information sources
Background: Many classification approaches have been applied to analyzing transcriptional regulation of gene expressions. These methods build models that can explain a gene's...
Jianhua Ruan, Weixiong Zhang
BMCBI
2005
112views more  BMCBI 2005»
13 years 4 months ago
Towards precise classification of cancers based on robust gene functional expression profiles
Background: Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. Th...
Zheng Guo, Tianwen Zhang, Xia Li, Qi Wang, Jianzhe...
IBPRIA
2007
Springer
13 years 8 months ago
Random Forest for Gene Expression Based Cancer Classification: Overlooked Issues
Random forest is a collection (ensemble) of decision trees. It is a popular ensemble technique in pattern recognition. In this article, we apply random forest for cancer classifica...
Oleg Okun, Helen Priisalu