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» Memetic Algorithms for Feature Selection on Microarray Data
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BIRD
2007
Springer
118views Bioinformatics» more  BIRD 2007»
13 years 11 months ago
Biological Network Inference Using Redundancy Analysis
The paper presents MRNet, an original method for inferring genetic networks from microarray data. This method is based on maximum relevance/minimum redundancy (MRMR), an effective ...
Patrick Emmanuel Meyer, Kevin Kontos, Gianluca Bon...
ACL
2012
11 years 10 months ago
Joint Feature Selection in Distributed Stochastic Learning for Large-Scale Discriminative Training in SMT
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
Patrick Simianer, Stefan Riezler, Chris Dyer
KAIS
2007
97views more  KAIS 2007»
13 years 7 months ago
Stability of feature selection algorithms: a study on high-dimensional spaces
With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive ...
Alexandros Kalousis, Julien Prados, Melanie Hilari...
ICPR
2008
IEEE
14 years 2 months ago
A feature selection algorithm for handwritten character recognition
We present a Genetic Algorithm based feature selection approach according to which feature subsets are represented by individuals of an evolving population. Evolution is controlle...
Luigi P. Cordella, Claudio De Stefano, Francesco F...
BMCBI
2008
167views more  BMCBI 2008»
13 years 7 months ago
Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classificat
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...
Michael Gormley, Aydin Tozeren