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» A clustering method that uses lossy aggregation of data
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CIBCB
2005
IEEE
14 years 2 months ago
Functional Distances for Genes Based on GO Feature Maps and their Application to Clustering
— With the invention of high throughput methods, researchers are capable of producing large amounts of biological data. During the analysis of such data, the need for a functiona...
Nora Speer, Holger Fröhlich, Christian Spieth...
CSDA
2010
105views more  CSDA 2010»
13 years 9 months ago
James-Stein shrinkage to improve k-means cluster analysis
We study a general algorithm to improve accuracy in cluster analysis that employs the James-Stein shrinkage effect in k-means clustering. We shrink the centroids of clusters towar...
Jinxin Gao, David B. Hitchcock
DATAMINE
1999
113views more  DATAMINE 1999»
13 years 9 months ago
A Fast Parallel Clustering Algorithm for Large Spatial Databases
The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper,...
Xiaowei Xu, Jochen Jäger, Hans-Peter Kriegel
VIS
2003
IEEE
121views Visualization» more  VIS 2003»
14 years 10 months ago
Hierarchical Clustering for Unstructured Volumetric Scalar Fields
We present a method to represent unstructured scalar fields at multiple levels of detail. Using a parallelizable classification algorithm to build a cluster hierarchy, we generate...
Christopher S. Co, Bjørn Heckel, Hans Hagen...
ICML
2010
IEEE
13 years 10 months ago
Power Iteration Clustering
We present a simple and scalable graph clustering method called power iteration clustering (PIC). PIC finds a very low-dimensional embedding of a dataset using truncated power ite...
Frank Lin, William W. Cohen