766 search results - page 49 / 154 » Clustering high dimensional data using subspace and projecte... |
ICCS
2005
Springer
14 years 2 months ago
2005
Springer
Existing methods for time series clustering rely on the actual data values can become impractical since the methods do not easily handle dataset with high dimensionality, missing v...
ICML
2004
IEEE
14 years 9 months ago
2004
IEEE
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
EXPDB
2006
ACM
14 years 2 months ago
2006
ACM
In data warehousing applications, the ability to efficiently delete large chunks of data from a table is very important. This feature is also known as Rollout. Rollout is generall...
SDM
2004
SIAM
13 years 10 months ago
2004
SIAM
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
GFKL
2004
Springer
14 years 2 months ago
2004
Springer
Abstract. A method for measuring the density of data sets that contain an unknown number of clusters of unknown sizes is proposed. This method, called Pareto Density Estimation (PD...