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» Feature Subset Selection and Ranking for Data Dimensionality...
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SDM
2010
SIAM
165views Data Mining» more  SDM 2010»
15 years 1 months ago
Direct Density Ratio Estimation with Dimensionality Reduction
Methods for directly estimating the ratio of two probability density functions without going through density estimation have been actively explored recently since they can be used...
Masashi Sugiyama, Satoshi Hara, Paul von Büna...
ICDE
2012
IEEE
246views Database» more  ICDE 2012»
13 years 2 months ago
HiCS: High Contrast Subspaces for Density-Based Outlier Ranking
—Outlier mining is a major task in data analysis. Outliers are objects that highly deviate from regular objects in their local neighborhood. Density-based outlier ranking methods...
Fabian Keller, Emmanuel Müller, Klemens B&oum...
JMLR
2010
165views more  JMLR 2010»
14 years 6 months ago
Feature Selection: An Ever Evolving Frontier in Data Mining
The rapid advance of computer technologies in data processing, collection, and storage has provided unparalleled opportunities to expand capabilities in production, services, comm...
Huan Liu, Hiroshi Motoda, Rudy Setiono, Zheng Zhao
CIBCB
2005
IEEE
15 years 5 months ago
Two-Phase EA/k-NN for Feature Selection and Classification in Cancer Microarray Datasets
Efficient and reliable methods that can find a small sample of informative genes amongst thousands are of great importance. In this area, much research is investigating the combina...
Thorhildur Juliusdottir, David Corne, Ed Keedwell,...
CIKM
2008
Springer
15 years 1 months ago
REDUS: finding reducible subspaces in high dimensional data
Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are...
Xiang Zhang, Feng Pan, Wei Wang 0010