220 search results - page 16 / 44 » Measures of Clustering Quality: A Working Set of Axioms for ... |
ISAAC
2009
Springer
14 years 2 months ago
2009
Springer
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
ICDE
2006
IEEE
14 years 9 months ago
2006
IEEE
In this paper, we propose a new model for coherent clustering of gene expression data called reg-cluster. The proposed model allows (1) the expression profiles of genes in a clust...
BIODATAMINING
2008
13 years 7 months ago
2008
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
ICALP
2009
Springer
14 years 7 months ago
2009
Springer
Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
IEEEVAST
2010
13 years 2 months ago
2010
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each ob...