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» Comparing Massive High-Dimensional Data Sets
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IDEAL
2005
Springer
13 years 11 months ago
Cluster Analysis of High-Dimensional Data: A Case Study
Abstract. Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular es...
Richard Bean, Geoffrey J. McLachlan
BMEI
2008
IEEE
13 years 8 months ago
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...
CCGRID
2010
IEEE
13 years 7 months ago
High Performance Dimension Reduction and Visualization for Large High-Dimensional Data Analysis
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...
Jong Youl Choi, Seung-Hee Bae, Xiaohong Qiu, Geoff...
ICDM
2009
IEEE
125views Data Mining» more  ICDM 2009»
14 years 28 days ago
A Fully Automated Method for Discovering Community Structures in High Dimensional Data
—Identifying modules, or natural communities, in large complex networks is fundamental in many fields, including social sciences, biological sciences and engineering. Recently s...
Jianhua Ruan
ADC
2003
Springer
123views Database» more  ADC 2003»
13 years 11 months ago
A Distance-Based Packing Method for High Dimensional Data
Minkowski-sum cost model indicates that balanced data partitioning is not beneficial for high dimensional data. Thus we study several unbalanced partitioning methods and propose ...
Tae-wan Kim, Ki-Joune Li