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ICGA
1997
133views Optimization» more  ICGA 1997»
15 years 5 months ago
Messy Genetic Algorithms for Subset Feature Selection
Subset Feature Selection problems can have severalattributes which may make Messy Genetic Algorithms an appropriateoptimization method. First, competitive solutions may often use ...
L. Darrell Whitley, J. Ross Beveridge, Cesar Guerr...
TITB
2008
136views more  TITB 2008»
15 years 4 months ago
Helicobacter Pylori-Related Gastric Histology Classification Using Support-Vector-Machine-Based Feature Selection
Abstract--This study presents a computer-aided diagnosis system using sequential forward floating selection (SFFS) with support vector machine (SVM) to diagnose gastric histology o...
Chun-Rong Huang, Pau-Choo Chung, Bor-Shyang Sheu, ...
ACL
2012
13 years 6 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
EWCBR
2004
Springer
15 years 9 months ago
Feature Selection and Generalisation for Retrieval of Textual Cases
Textual CBR systems solve problems by reusing experiences that are in textual form. Knowledge-rich comparison of textual cases remains an important challenge for these systems. How...
Nirmalie Wiratunga, Ivan Koychev, Stewart Massie
GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
15 years 10 months ago
Evolutionary selection of minimum number of features for classification of gene expression data using genetic algorithms
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
Alper Küçükural, Reyyan Yeniterzi...