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ICML
2004
IEEE
15 years 12 months ago
Redundant feature elimination for multi-class problems
We consider the problem of eliminating redundant Boolean features for a given data set, where a feature is redundant if it separates the classes less well than another feature or ...
Annalisa Appice, Michelangelo Ceci, Simon Rawles, ...
ILP
2003
Springer
15 years 11 months ago
A Comparative Evaluation of Feature Set Evolution Strategies for Multirelational Boosting
Boosting has established itself as a successful technique for decreasing the generalization error of classification learners by basing predictions on ensembles of hypotheses. Whil...
Susanne Hoche, Stefan Wrobel
ICML
2004
IEEE
16 years 7 months ago
Robust feature induction for support vector machines
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...
Rong Jin, Huan Liu
CVPR
2007
IEEE
16 years 8 months ago
Boosting Coded Dynamic Features for Facial Action Units and Facial Expression Recognition
It is well known that how to extract dynamical features is a key issue for video based face analysis. In this paper, we present a novel approach of facial action units (AU) and ex...
Peng Yang, Qingshan Liu, Dimitris N. Metaxas
SAC
2006
ACM
16 years 14 days 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