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» Landscape of Clustering Algorithms
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BMCBI
2008
122views more  BMCBI 2008»
13 years 11 months ago
A practical comparison of two K-Means clustering algorithms
Background: Data clustering is a powerful technique for identifying data with similar characteristics, such as genes with similar expression patterns. However, not all implementat...
Gregory A. Wilkin, Xiuzhen Huang
DAWAK
2007
Springer
14 years 5 months ago
MOSAIC: A Proximity Graph Approach for Agglomerative Clustering
Representative-based clustering algorithms are quite popular due to their relative high speed and because of their sound theoretical foundation. On the other hand, the clusters the...
Jiyeon Choo, Rachsuda Jiamthapthaksin, Chun-Sheng ...
CSB
2005
IEEE
115views Bioinformatics» more  CSB 2005»
14 years 4 months ago
A New Clustering Strategy with Stochastic Merging and Removing Based on Kernel Functions
With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they c...
Huimin Geng, Hesham H. Ali
KDD
2002
ACM
166views Data Mining» more  KDD 2002»
14 years 11 months ago
Frequent term-based text clustering
Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special p...
Florian Beil, Martin Ester, Xiaowei Xu
UAI
1998
14 years 7 days ago
An Experimental Comparison of Several Clustering and Initialization Methods
We examine methods for clustering in high dimensions. In the first part of the paper, we perform an experimental comparison between three batch clustering algorithms: the Expectat...
Marina Meila, David Heckerman