244 search results - page 4 / 49 » Feature selection for high-dimensional genomic microarray da... |
ICDE
2008
IEEE
14 years 8 months ago
2008
IEEE
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
BMCBI
2007
13 years 7 months ago
2007
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
SDM
2009
SIAM
14 years 4 months ago
2009
SIAM
Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
IDEAL
2007
Springer
14 years 1 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...
BMCBI
2010
13 years 7 months ago
2010
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...