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» Parallelizing Feature Selection
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PAMI
2010
276views more  PAMI 2010»
14 years 8 months ago
Local-Learning-Based Feature Selection for High-Dimensional Data Analysis
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
Yijun Sun, Sinisa Todorovic, Steve Goodison
CIKM
2009
Springer
15 years 4 months ago
Feature selection for ranking using boosted trees
Modern search engines have to be fast to satisfy users, so there are hard back-end latency requirements. The set of features useful for search ranking functions, though, continues...
Feng Pan, Tim Converse, David Ahn, Franco Salvetti...
SAC
2006
ACM
15 years 3 months ago
Exploiting partial decision trees for feature subset selection in e-mail categorization
In this paper we propose PARTfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. In particular, it is...
Helmut Berger, Dieter Merkl, Michael Dittenbach
EUROCAST
2003
Springer
134views Hardware» more  EUROCAST 2003»
15 years 3 months ago
Volumetric Texture Description and Discriminant Feature Selection for MRI
This paper considers the problem of texture description and feature selection for the classification of tissues in 3D Magnetic Resonance data. Joint statistical measures like grey...
Abhir Bhalerao, Constantino Carlos Reyes-Aldasoro
TIP
2011
137views more  TIP 2011»
14 years 4 months ago
Boosting Color Feature Selection for Color Face Recognition
—This paper introduces the new color face recognition (FR) method that makes effective use of boosting learning as color-component feature selection framework. The proposed boost...
Jae Young Choi, Yong Man Ro, Konstantinos N. Plata...