180 search results - page 4 / 36 » Generalized Projected Clustering in High-Dimensional Data St... |
SDM
2003
SIAM
13 years 7 months ago
2003
SIAM
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
AAAI
2006
13 years 7 months ago
2006
Among various feature extraction algorithms, those based on genetic algorithms are promising owing to their potential parallelizability and possible applications in large scale an...
ICDM
2003
IEEE
13 years 11 months ago
2003
IEEE
We are proposing a novel method that makes it possible to analyze high dimensional data with arbitrary shaped projected clusters and high noise levels. At the core of our method l...
PAKDD
2009
ACM
14 years 17 days ago
2009
ACM
Abstract. Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To addre...
PAKDD
2005
ACM
13 years 11 months ago
2005
ACM
In many modern application ranges high-dimensional feature vectors are used to model complex real-world objects. Often these objects reside on different local sites. In this paper,...