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BMCBI
2007
194views more  BMCBI 2007»
13 years 8 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
EUROGP
2004
Springer
133views Optimization» more  EUROGP 2004»
14 years 1 months ago
Lymphoma Cancer Classification Using Genetic Programming with SNR Features
Lymphoma cancer classification with DNA microarray data is one of important problems in bioinformatics. Many machine learning techniques have been applied to the problem and produc...
Jin-Hyuk Hong, Sung-Bae Cho
ALMOB
2007
133views more  ALMOB 2007»
13 years 8 months ago
Characteristics of predictor sets found using differential prioritization
Background: Feature selection plays an undeniably important role in classification problems involving high dimensional datasets such as microarray datasets. For filter-based featu...
Chia Huey Ooi, Madhu Chetty, Shyh Wei Teng
BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
13 years 8 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty
PR
2006
229views more  PR 2006»
13 years 7 months ago
FS_SFS: A novel feature selection method for support vector machines
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
Yi Liu, Yuan F. Zheng