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» Feature selection based on the training set manipulation
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IWANN
2005
Springer
14 years 1 months ago
Heuristic Search over a Ranking for Feature Selection
In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited feature set for distinguishing experiment classes in hig...
Roberto Ruiz, José Cristóbal Riquelm...
BMCBI
2008
106views more  BMCBI 2008»
13 years 7 months ago
A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selec
Background: Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnologica...
Ning Wei, Erwin Flaschel, Karl Friehs, Tim W. Natt...
JMLR
2011
110views more  JMLR 2011»
13 years 2 months ago
Training SVMs Without Offset
We develop, analyze, and test a training algorithm for support vector machine classifiers without offset. Key features of this algorithm are a new, statistically motivated stoppi...
Ingo Steinwart, Don R. Hush, Clint Scovel
IJCV
2006
206views more  IJCV 2006»
13 years 7 months ago
Random Sampling for Subspace Face Recognition
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...
Xiaogang Wang, Xiaoou Tang
CSB
2005
IEEE
143views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Multivariate gene selection: Does it help
When building predictors of disease state based on gene expression data, gene selection is performed in order to achieve a good performance and to identify a relevant subset of ge...
Carmen Lai, Marcel J. T. Reinders