962 search results - page 11 / 193 » Redundancy based feature selection for microarray data |
CIKM
2010
Springer
14 years 7 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, ...
84
Voted
INCDM
2010
Springer
14 years 7 months ago
2010
Springer
In this paper we report on a study on feature selection within the minimum
95
Voted
TKDE
2008
14 years 9 months ago
2008
Abstract-- Feature selection is an important method for improving the efficiency and accuracy of text categorization algorithms by removing redundant and irrelevant terms from the ...
IDEAL
2007
Springer
15 years 3 months ago
2007
Springer
We apply learning vector quantization to the analysis of tiling microarray data. As an example we consider the classification of C. elegans genomic probes as intronic or exonic. T...
PKDD
2009
Springer
15 years 4 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...