Sciweavers

KAIS
2007
97views more  KAIS 2007»
13 years 3 months ago
Stability of feature selection algorithms: a study on high-dimensional spaces
With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive ...
Alexandros Kalousis, Julien Prados, Melanie Hilari...
AI
2004
Springer
13 years 3 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu
TKDE
2008
115views more  TKDE 2008»
13 years 3 months ago
A Niching Memetic Algorithm for Simultaneous Clustering and Feature Selection
Clustering is inherently a difficult task and is made even more difficult when the selection of relevant features is also an issue. In this paper, we propose an approach for simult...
Weiguo Sheng, Xiaohui Liu, Michael C. Fairhurst
TKDE
2008
111views more  TKDE 2008»
13 years 3 months ago
Text Clustering with Feature Selection by Using Statistical Data
Abstract-- Feature selection is an important method for improving the efficiency and accuracy of text categorization algorithms by removing redundant and irrelevant terms from the ...
Yanjun Li, Congnan Luo, Soon M. Chung
BMCBI
2005
118views more  BMCBI 2005»
13 years 3 months ago
Feature selection and nearest centroid classification for protein mass spectrometry
Background: The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard super...
Ilya Levner
PRL
2006
130views more  PRL 2006»
13 years 3 months ago
Efficient huge-scale feature selection with speciated genetic algorithm
With increasing interest in bioinformatics, sophisticated tools are required to efficiently analyze gene information. The classification of gene expression profiles is crucial in ...
Jin-Hyuk Hong, Sung-Bae Cho
PR
2006
111views more  PR 2006»
13 years 3 months ago
The Bhattacharyya space for feature selection and its application to texture segmentation
A feature selection methodology based on a novel Bhattacharyya space is presented and illustrated with a texture segmentation problem. The Bhattacharyya space is constructed from ...
Constantino Carlos Reyes-Aldasoro, Abhir Bhalerao
PR
2006
229views more  PR 2006»
13 years 3 months ago
FS_SFS: A novel feature selection method for support vector machines
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
Yi Liu, Yuan F. Zheng
PAA
2006
13 years 3 months ago
Classifier-independent feature selection on the basis of divergence criterion
Feature selection aims to choose a feature subset that has the most discriminative information from the original feature set. In practical cases, it is preferable to select a featu...
Naoto Abe, Mineichi Kudo, Jun Toyama, Masaru Shimb...
PR
2008
151views more  PR 2008»
13 years 3 months ago
Constraint Score: A new filter method for feature selection with pairwise constraints
Feature selection is an important preprocessing step in mining high-dimensional data. Generally, supervised feature selection methods with supervision information are superior to ...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou