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PRL
2006
121views more  PRL 2006»
13 years 7 months ago
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Data reduction plays an important role in machine learning and pattern recognition with a high-dimensional data. In real-world applications data usually exists with hybrid formats...
Qinghua Hu, Daren Yu, Zongxia Xie
BMCBI
2008
157views more  BMCBI 2008»
13 years 7 months ago
Dimension reduction with redundant gene elimination for tumor classification
Background: Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DN...
Xue-Qiang Zeng, Guo-Zheng Li, Jack Y. Yang, Mary Q...
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
14 years 8 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
MM
2010
ACM
238views Multimedia» more  MM 2010»
13 years 7 months ago
Supervised manifold learning for image and video classification
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
Yang Liu, Yan Liu, Keith C. C. Chan
ACMACE
2008
ACM
13 years 9 months ago
Dimensionality reduced HRTFs: a comparative study
Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
Bill Kapralos, Nathan Mekuz, Agnieszka Kopinska, S...