21 search results - page 2 / 5 » Comparison of Poisson Mixture Models for Count Data Clusteri... |
ICPR
2008
IEEE
14 years 2 days ago
2008
IEEE
In this paper we propose a new clustering algorithm which combines the FCM clustering algorithm with the supervised learning normal mixture model; we call the algorithm as the FCM...
GFKL
2005
Springer
13 years 11 months ago
2005
Springer
Mixture models represent results of gene expression cluster analysis in a more natural way than ’hard’ partitions. This is also true for the representation of gene labels, such...
KDD
2010
ACM
13 years 3 months ago
2010
ACM
One essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. In this paper, we ...
BMCBI
2008
13 years 5 months ago
2008
Background: Tight clustering arose recently from a desire to obtain tighter and potentially more informative clusters in gene expression studies. Scattered genes with relatively l...
NIPS
2007
13 years 7 months ago
2007
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...