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BMCBI
2008
169views more  BMCBI 2008»
13 years 6 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...
CEC
2007
IEEE
13 years 10 months ago
Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms
In this work we compare the use of a Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA) (both augmented with Support Vector Machines SVM) for the classification of high...
Enrique Alba, José García-Nieto, Lae...
BMCBI
2006
158views more  BMCBI 2006»
13 years 6 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
BMCBI
2005
167views more  BMCBI 2005»
13 years 6 months ago
Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes
Background: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer...
Patrick Warnat, Roland Eils, Benedikt Brors
APBC
2003
128views Bioinformatics» more  APBC 2003»
13 years 7 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won