56 search results - page 2 / 12 » DBDC: Density Based Distributed Clustering |
PKDD
2004
Springer
14 years 14 days ago
2004
Springer
Clustering has become an increasingly important task in analysing huge amounts of data. Traditional applications require that all data has to be located at the site where it is scr...
ICASSP
2011
IEEE
12 years 10 months ago
2011
IEEE
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
CVPR
2005
IEEE
14 years 9 months ago
2005
IEEE
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
PAKDD
2005
ACM
14 years 18 days ago
2005
ACM
Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...
ICPR
2008
IEEE
14 years 8 months ago
2008
IEEE
In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...