32 search results - page 1 / 7 » Partially supervised feature selection with regularized line... |
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...
PKDD
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervisio...
JMLR
2010
12 years 11 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...
CIKM
2011
Springer
12 years 4 months ago
2011
Springer
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
CIKM
2010
Springer
13 years 2 months ago
2010
Springer
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...