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BMCBI
2008
122views more  BMCBI 2008»
15 years 2 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
MICRO
2002
IEEE
143views Hardware» more  MICRO 2002»
15 years 6 months ago
Effective instruction scheduling techniques for an interleaved cache clustered VLIW processor
Clustering is a common technique to overcome the wire delay problem incurred by the evolution of technology. Fully-distributed architectures, where the register file, the functio...
Enric Gibert, F. Jesús Sánchez, Anto...
CVPR
2003
IEEE
16 years 4 months ago
Robust Data Clustering
We address the problem of robust clustering by combining data partitions (forming a clustering ensemble) produced by multiple clusterings. We formulate robust clustering under an ...
Ana L. N. Fred, Anil K. Jain
IJKDB
2010
170views more  IJKDB 2010»
14 years 11 months ago
Clustering Genes Using Heterogeneous Data Sources
Clustering of gene expression data is a standard exploratory technique used to identify closely related genes. Many other sources of data are also likely to be of great assistance...
Erliang Zeng, Chengyong Yang, Tao Li, Giri Narasim...
MLDM
2005
Springer
15 years 7 months ago
Supervised Evaluation of Dataset Partitions: Advantages and Practice
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...
Sylvain Ferrandiz, Marc Boullé