434 search results - page 4 / 87 » Dimensionality Reduction of Clustered Data Sets |
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
ICDM
2002
IEEE
14 years 11 days ago
2002
IEEE
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
AUSDM
2007
Springer
14 years 1 months ago
2007
Springer
One of the inherent problems in pattern recognition is the undersampled data problem, also known as the curse of dimensionality reduction. In this paper a new algorithm called pai...
PRL
2006
13 years 7 months ago
2006
In this paper, we present a wavelet based approach which tries to automatically find the number of clusters present in a data set, along with their position and statistical proper...
ICDM
2002
IEEE
14 years 11 days ago
2002
IEEE
Clustering large data sets of high dimensionality has always been a serious challenge for clustering algorithms. Many recently developed clustering algorithms have attempted to ad...