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» Efficient Spectral Feature Selection with Minimum Redundancy
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PRL
2006
130views more  PRL 2006»
13 years 5 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
GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
13 years 12 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...
ICAPR
2009
Springer
14 years 11 days ago
Relevant and Redundant Feature Analysis with Ensemble Classification
— Feature selection and ensemble classification increase system efficiency and accuracy in machine learning, data mining and biomedical informatics. This research presents an ana...
Rakkrit Duangsoithong, Terry Windeatt
INTERSPEECH
2010
13 years 19 days ago
Efficient HMM-based estimation of missing features, with applications to packet loss concealment
In this paper, we present efficient HMM-based techniques for estimating missing features. By assuming speech features to be observations of hidden Markov processes, we derive a mi...
Bengt J. Borgström, Per Henrik Borgström...
CSB
2005
IEEE
133views Bioinformatics» more  CSB 2005»
13 years 11 months ago
Choosing SNPs Using Feature Selection
A major challenge for genomewide disease association studies is the high cost of genotyping large number of single nucleotide polymorphisms (SNP). The correlations between SNPs, h...
Tu Minh Phuong, Zhen Lin, Russ B. Altman