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» An Experiment with Distance Measures for Clustering
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BIOINFORMATICS
2007
137views more  BIOINFORMATICS 2007»
14 years 9 months ago
Annotation-based distance measures for patient subgroup discovery in clinical microarray studies
: Background Clustering algorithms are widely used in the analysis of microarray data. In clinical studies, they are often applied to find groups of co-regulated genes. Clustering...
Claudio Lottaz, Joern Toedling, Rainer Spang
PAMI
2008
197views more  PAMI 2008»
14 years 9 months ago
LEGClust - A Clustering Algorithm Based on Layered Entropic Subgraphs
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...
ICDM
2005
IEEE
190views Data Mining» more  ICDM 2005»
15 years 3 months ago
Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past Experience
Adaptive clustering uses external feedback to improve cluster quality; past experience serves to speed up execution time. An adaptive clustering environment is proposed that uses ...
Abraham Bagherjeiran, Christoph F. Eick, Chun-Shen...
BMCBI
2007
116views more  BMCBI 2007»
14 years 9 months ago
Ranked Adjusted Rand: integrating distance and partition information in a measure of clustering agreement
Background: Biological information is commonly used to cluster or classify entities of interest such as genes, conditions, species or samples. However, different sources of data c...
Francisco R. Pinto, João A. Carriço,...
ICIAP
1999
ACM
15 years 1 months ago
Texture Segmentation by Frequency-Sensitive Elliptical Competitive Learning
In this paper a new learning algorithm is proposed with the purpose of texture segmentation. The algorithm is a competitive clustering scheme with two specific features: elliptic...
Steve De Backer, Paul Scheunders