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» Dimensionality Reduction of Clustered Data Sets
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JPDC
2008
134views more  JPDC 2008»
13 years 8 months ago
Middleware for data mining applications on clusters and grids
This paper gives an overview of two middleware systems that have been developed over the last 6 years to address the challenges involved in developing parallel and distributed imp...
Leonid Glimcher, Ruoming Jin, Gagan Agrawal
FUZZIEEE
2007
IEEE
14 years 3 months ago
Distance Measure Assisted Rough Set Feature Selection
Abstract— Feature Selection (FS) is a technique for dimensionality reduction. Its aims are to select a subset of the original features of a dataset which are rich in the most use...
Neil MacParthalain, Qiang Shen, Richard Jensen
BMCBI
2002
195views more  BMCBI 2002»
13 years 8 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
ICDE
1998
IEEE
163views Database» more  ICDE 1998»
14 years 10 months ago
Fast Nearest Neighbor Search in High-Dimensional Space
Similarity search in multimedia databases requires an efficient support of nearest-neighbor search on a large set of high-dimensional points as a basic operation for query process...
Stefan Berchtold, Bernhard Ertl, Daniel A. Keim, H...
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
14 years 9 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler