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PRL
2006
130views more  PRL 2006»
13 years 7 months ago
Efficient huge-scale feature selection with speciated genetic algorithm
With increasing interest in bioinformatics, sophisticated tools are required to efficiently analyze gene information. The classification of gene expression profiles is crucial in ...
Jin-Hyuk Hong, Sung-Bae Cho
MVA
1996
13 years 8 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
SSPR
2004
Springer
14 years 22 days ago
Optimizing Classification Ensembles via a Genetic Algorithm for a Web-Based Educational System
Classification fusion combines multiple classifications of data into a single classification solution of greater accuracy. Feature extraction aims to reduce the computational cost ...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...
HAIS
2009
Springer
14 years 8 hour ago
Unsupervised Feature Selection in High Dimensional Spaces and Uncertainty
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...
José Ramón Villar, María del ...
SGAI
2004
Springer
14 years 22 days ago
Overfitting in Wrapper-Based Feature Subset Selection: The Harder You Try the Worse it Gets
In Wrapper based feature selection, the more states that are visited during the search phase of the algorithm the greater the likelihood of finding a feature subset that has a high...
John Loughrey, Padraig Cunningham