38 search results - page 1 / 8 » Robust clustering in high dimensional data using statistical... |
BMCBI
2007
13 years 4 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...
CORR
2010
Springer
13 years 4 months ago
2010
Springer
: Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerate...
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
We investigate how random projection can best be used for clustering high dimensional data. Random projection has been shown to have promising theoretical properties. In practice,...
MLDM
2005
Springer
13 years 10 months ago
2005
Springer
Subspace clustering is an extension of traditional clustering that seeks to find clusters in different subspaces within a dataset. This is a particularly important challenge with...
BMEI
2008
IEEE
13 years 6 months ago
2008
IEEE
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...