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APWEB
2006
Springer
13 years 8 months ago
Generalized Projected Clustering in High-Dimensional Data Streams
Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...
Ting Wang
TVCG
2011
152views more  TVCG 2011»
12 years 11 months ago
Automated Analytical Methods to Support Visual Exploration of High-Dimensional Data
—Visual exploration of multivariate data typically requires projection onto lower-dimensional representations. The number of possible representations grows rapidly with the numbe...
Andrada Tatu, Georgia Albuquerque, Martin Eisemann...
NIPS
2003
13 years 6 months ago
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Neil D. Lawrence
DMIN
2008
152views Data Mining» more  DMIN 2008»
13 years 6 months ago
PCS: An Efficient Clustering Method for High-Dimensional Data
Clustering algorithms play an important role in data analysis and information retrieval. How to obtain a clustering for a large set of highdimensional data suitable for database ap...
Wei Li 0011, Cindy Chen, Jie Wang
BMCBI
2007
123views more  BMCBI 2007»
13 years 4 months ago
Robust clustering in high dimensional data using statistical depths
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
Yuanyuan Ding, Xin Dang, Hanxiang Peng, Dawn Wilki...