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BMCBI
2008
160views more  BMCBI 2008»
14 years 9 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...
ICCBR
2003
Springer
15 years 2 months ago
Unifying Weighting and Case Reduction Methods Based on Rough Sets to Improve Retrieval
Case-Based Reasoning systems usually retrieve cases using a similarity function based on K-NN or some derivatives. These functions are sensitive to irrelevant or noisy features. We...
Maria Salamó, Elisabet Golobardes
MVA
1996
14 years 10 months ago
Inductive Learning of Primitive Shape Features of Closed Contours
A method for inductivelearningof primitive features is proposed. Primitive features are well investigated and they are extracted in bottom-up manner fiom training set of patterns ...
Ichiro Murase, Shun'ichi Kaneko, Satoru Igarashi
BMCBI
2010
208views more  BMCBI 2010»
14 years 9 months ago
A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
BMCBI
2006
167views more  BMCBI 2006»
14 years 9 months ago
GOurmet: A tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributi
Background: The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental conditions is an important but difficu...
Jason M. Doherty, Lynn K. Carmichael, Jason C. Mil...