165 search results - page 2 / 33 » Adaptive dimension reduction for clustering high dimensional... |
CCGRID
2010
IEEE
13 years 5 months ago
2010
IEEE
Abstract--Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for understanding the results of data mining appro...
ICCS
2005
Springer
13 years 10 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...
SDM
2004
SIAM
13 years 6 months ago
2004
SIAM
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
BMCBI
2010
13 years 4 months ago
2010
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
PAMI
2006
13 years 4 months ago
2006
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...