33 search results - page 2 / 7 » Kernel-based distance metric learning for microarray data cl... |
97
Voted
APBC
2003
14 years 11 months ago
2003
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
75
Voted
ICML
2010
IEEE
14 years 11 months ago
2010
IEEE
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
106
Voted
BMCBI
2011
14 years 1 months ago
2011
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
113
Voted
BMCBI
2006
14 years 10 months ago
2006
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
96
Voted
ECML
2006
Springer
15 years 1 months ago
2006
Springer
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...