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» Messy Genetic Algorithms for Subset Feature Selection
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DMIN
2007
203views Data Mining» more  DMIN 2007»
13 years 10 months ago
Evaluation of Feature Selection Techniques for Analysis of Functional MRI and EEG
— The application of feature selection techniques greatly reduces the computational cost of classifying highdimensional data. Feature selection algorithms of varying performance ...
Lauren Burrell, Otis Smart, George J. Georgoulas, ...
GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
14 years 3 months ago
Crossover operators for multiobjective k-subset selection
Genetic algorithms are often applied to combinatorial optimization problems, the most popular one probably being the traveling salesperson problem. In contrast to permutations use...
Thorsten Meinl, Michael R. Berthold
AE
2007
Springer
14 years 2 months ago
A Study of Crossover Operators for Gene Selection of Microarray Data
Classification of microarray data requires the selection of a subset of relevant genes in order to achieve good classification performance. Several genetic algorithms have been d...
Jose Crispin Hernandez Hernandez, Béatrice ...
GPEM
2007
119views more  GPEM 2007»
13 years 8 months ago
Genomic mining for complex disease traits with "random chemistry"
Our rapidly growing knowledge regarding genetic variation in the human genome offers great potential for understanding the genetic etiology of disease. This, in turn, could revolut...
Margaret J. Eppstein, Joshua L. Payne, Bill C. Whi...
ICONIP
2008
13 years 10 months ago
Local Feature Selection in Text Clustering
Abstract. Feature selection has improved the performance of text clustering. Global feature selection tries to identify a single subset of features which are relevant to all cluste...
Marcelo N. Ribeiro, Manoel J. R. Neto, Ricardo Bas...