921 search results - page 21 / 185 » Feature selection in scientific applications |
ICASSP
2007
IEEE
14 years 4 months ago
2007
IEEE
This paper proposes a novel feature selection method based on twostage analysis of Fisher Ratio and Mutual Information for robust Brain Computer Interface. This method decomposes ...
JMLR
2010
13 years 4 months ago
2010
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
DAGSTUHL
2009
13 years 11 months ago
2009
The selection of features that are relevant for a prediction or classification problem is an important problem in many domains involving high-dimensional data. Selecting features h...
PR
2006
13 years 9 months ago
2006
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
GECCO
2007
Springer
14 years 4 months ago
2007
Springer
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...