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» Lossy Reduction for Very High Dimensional Data
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CIKM
2003
Springer
13 years 10 months ago
Dimensionality reduction using magnitude and shape approximations
High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
Ümit Y. Ogras, Hakan Ferhatosmanoglu
ADMA
2008
Springer
124views Data Mining» more  ADMA 2008»
13 years 7 months ago
Dimensionality Reduction for Classification
We investigate the effects of dimensionality reduction using different techniques and different dimensions on six two-class data sets with numerical attributes as pre-processing fo...
Frank Plastria, Steven De Bruyne, Emilio Carrizosa
ICIP
2006
IEEE
14 years 6 months ago
Lossy-To-Lossless Block-Based Compression of Hyperspectral Volumetric Data
An embedded, block-based, wavelet transform coding algorithm of low complexity is proposed. Three-Dimensional Set Partitioned Embedded bloCK(3D-SPECK) efficiently encodes hyperspe...
Xiaoli Tang, William A. Pearlman
ICDM
2008
IEEE
164views Data Mining» more  ICDM 2008»
13 years 11 months ago
Classifying High-Dimensional Text and Web Data Using Very Short Patterns
In this paper, we propose the "Democratic Classifier", a simple, democracy-inspired patternbased classification algorithm that uses very short patterns for classificatio...
Hassan H. Malik, John R. Kender