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EVOW
2006
Springer
13 years 9 months ago
A Hybrid GA/SVM Approach for Gene Selection and Classification of Microarray Data
We propose a Genetic Algorithm (GA) approach combined with Support Vector Machines (SVM) for the classification of high dimensional Microarray data. This approach is associated to ...
Edmundo Bonilla Huerta, Béatrice Duval, Jin...
BMCBI
2008
169views more  BMCBI 2008»
13 years 5 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
PRL
2006
130views more  PRL 2006»
13 years 5 months ago
Efficient huge-scale feature selection with speciated genetic algorithm
With increasing interest in bioinformatics, sophisticated tools are required to efficiently analyze gene information. The classification of gene expression profiles is crucial in ...
Jin-Hyuk Hong, Sung-Bae Cho
ACSC
2005
IEEE
13 years 11 months ago
Integer Programming Models and Algorithms for Molecular Classification of Cancer from Microarray Data
Novel, high-throughput technologies are challenging the core of algorithmic methods available in Computer Science. Microarray technologies give Life Sciences researchers the oppor...
Regina Berretta, Alexandre Mendes, Pablo Moscato
IJBRA
2007
97views more  IJBRA 2007»
13 years 5 months ago
Structural Risk Minimisation based gene expression profiling analysis
: For microarray based cancer classification, feature selection is a common method for improving classifier generalisation. Most wrapper methods use cross validation methods to eva...
Xue-wen Chen, Byron Gerlach, Dechang Chen, ZhenQiu...