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» On the Complexity of Ordinal Clustering
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BMCBI
2007
173views more  BMCBI 2007»
13 years 9 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
13 years 6 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu
COCOON
2009
Springer
14 years 3 months ago
Graph-Based Data Clustering with Overlaps
We introduce overlap cluster graph modification problems where, other than in most previous work, the clusters of the target graph may overlap. More precisely, the studied graph p...
Michael R. Fellows, Jiong Guo, Christian Komusiewi...
SSDBM
2000
IEEE
87views Database» more  SSDBM 2000»
14 years 1 months ago
A Tool for Nesting and Clustering Large Objects
In implementations of non-standard database systems, large objects are often embedded within an aggregate of different types, i.e. a tuple. For a given size and access probabilit...
Stefan Dieker, Ralf Hartmut Güting, Miguel Ro...
NIPS
2007
13 years 10 months ago
Consistent Minimization of Clustering Objective Functions
Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....
Ulrike von Luxburg, Sébastien Bubeck, Stefa...