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» Hierarchical exploration of large multivariate data sets
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KDD
1997
ACM
143views Data Mining» more  KDD 1997»
15 years 1 months ago
Anytime Exploratory Data Analysis for Massive Data Sets
Exploratory data analysis is inherently an iterative, interactive endeavor. In the context of massive data sets, however, many current data analysis algorithms will not scale appr...
Padhraic Smyth, David Wolpert
90
Voted
ICDM
2006
IEEE
161views Data Mining» more  ICDM 2006»
15 years 3 months ago
Hierarchical Density Shaving: A clustering and visualization framework for large biological datasets
In many clustering applications for bioinformatics, only part of the data clusters into one or more groups while the rest needs to be pruned. For such situations, we present Hiera...
Gunjan Gupta, Alexander Liu, Joydeep Ghosh
PAMI
1998
128views more  PAMI 1998»
14 years 9 months ago
A Hierarchical Latent Variable Model for Data Visualization
—Visualization has proven to be a powerful and widely-applicable tool for the analysis and interpretation of multivariate data. Most visualization algorithms aim to find a projec...
Christopher M. Bishop, Michael E. Tipping
BMCBI
2011
14 years 4 months ago
Multivariate analysis of microarray data: differential expression and differential connection
Background: Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically all...
Harri T. Kiiveri
BMCBI
2006
154views more  BMCBI 2006»
14 years 9 months ago
Analysis with respect to instrumental variables for the exploration of microarray data structures
Background: Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various fa...
Florent Baty, Michaël Facompré, Jan Wi...