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SADM
2011
15 years 1 months ago
Random survival forests for high-dimensional data
: Minimal depth is a dimensionless order statistic that measures the predictiveness of a variable in a survival tree. It can be used to select variables in high-dimensional problem...
Hemant Ishwaran, Udaya B. Kogalur, Xi Chen, Andy J...
BMEI
2008
IEEE
15 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...
KDD
2004
ACM
314views Data Mining» more  KDD 2004»
16 years 7 months ago
Assessment of discretization techniques for relevant pattern discovery from gene expression data
In the domain of gene expression data analysis, various researchers have recently emphasized the promising application of pattern discovery techniques like association rule mining...
Ruggero G. Pensa, Claire Leschi, Jéré...
AVI
2004
15 years 8 months ago
SWAPit: a multiple views paradigm for exploring associations of texts and structured data
Visualization interfaces that offer multiple coordinated views on a particular set of data items are useful for navigating and exploring complex information spaces. In this paper ...
Andreas Becks, Christian Seeling
CIMCA
2005
IEEE
16 years 7 days ago
Modeling the Cross-Cultural Adaptation Process of Immigrants Using Categorical Data Clustering
— This paper introduces a quantitative method for social data analysis, which is based on the use of categorical data clustering. More specifically, we employ categorical data cl...
George E. Tsekouras