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Clustering high-dimensional data

Clustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions. Such high-dimensional spaces of data are often encountered in areas such as medicine, where DNA microarray technology can produce many measurements at once, and the clustering of text documents, where, if a word-frequency…

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Clustering high-dimensional data

Nodes33
Edges32
Triples9
Avg. degree1.94
Density0.060606
Components1

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Clustering high-dimensional data

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Clustering high-dimensional data → cluster analysis of data with anywhere from a few dozen to many thousands of dimensions

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clustering data dimensions subspaces clusters cluster high-dimensional subspace number used distance different approach space algorithm many attributes approaches two points

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SubjectPredicateObjectConfidenceSrc
Clustering high-dimensional datais acluster analysis of data with anywhere from a few dozen to many thousands of dimensions0.90text
medicineinstance ofSuch high-dimensional spaces of data are often encountered in areas0.80text
where DNA microarray technology can produce many measurements at onceinstance ofSuch high-dimensional spaces of data are often encountered in areas0.80text
and the clustering of text documentsinstance ofSuch high-dimensional spaces of data are often encountered in areas0.80text
whereinstance ofSuch high-dimensional spaces of data are often encountered in areas0.80text
if a word-frequency vector is usedinstance ofSuch high-dimensional spaces of data are often encountered in areas0.80text
the number of dimensions equals the size of the vocabularyinstance ofSuch high-dimensional spaces of data are often encountered in areas0.80text
CLIQUEinstance ofan approach taken by most of the traditional algorithms0.80text
SUBCLUinstance ofan approach taken by most of the traditional algorithms0.80text

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