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» Redundancy based feature selection for microarray data
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BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
14 years 9 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
68
Voted
JRTIP
2006
114views more  JRTIP 2006»
14 years 9 months ago
Sensor band selection for multispectral imaging via average normalized information
The information-rich scene descriptors created by multispectral sensors can act as a bottleneck in further analysis. Many of the spectral band selection methods treat the two under...
Hongzhi Wang, Elli Angelopoulou
BMCBI
2011
14 years 4 months ago
Sequential Interim Analyses of Survival Data in DNA Microarray Experiments
Background: Discovery of biomarkers that are correlated with therapy response and thus with survival is an important goal of medical research on severe diseases, e.g. cancer. Freq...
Andreas Leha, Tim Beißbarth, Klaus Jung
AI
2004
Springer
14 years 9 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu
90
Voted
BMCBI
2010
136views more  BMCBI 2010»
14 years 9 months ago
The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays
Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, producti...
Yevhen Vainshtein, Mayka Sanchez, Alvis Brazma, Ma...