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MLDM
2005
Springer
16 years 11 days ago
Using Clustering to Learn Distance Functions for Supervised Similarity Assessment
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...
ALMOB
2008
112views more  ALMOB 2008»
15 years 7 months ago
Metabolite-based clustering and visualization of mass spectrometry data using one-dimensional self-organizing maps
Background: One of the goals of global metabolomic analysis is to identify metabolic markers that are hidden within a large background of data originating from high-throughput ana...
Peter Meinicke, Thomas Lingner, Alexander Kaever, ...
BMCBI
2010
151views more  BMCBI 2010»
15 years 7 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
BMCBI
2006
163views more  BMCBI 2006»
15 years 7 months ago
Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological featur
Background: Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a userdefined list of genes and/or proteins. The strategy exploits annotation data ...
J. R. Semeiks, A. Rizki, Mina J. Bissell, I. Saira...
ICIP
2009
IEEE
16 years 8 months ago
Localized Null Space Representation For Dynamic Updating And Downdating In Image And Video Databases
Event/object classification and recognition is an extremely challenging problem, particularly when the query or stored data undergo an affine transformation due to camera motion. ...