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IJCNN
2006
IEEE
13 years 10 months ago
Semi-supervised feature selection via multiobjective optimization
Abstract— In previous work, we have shown that both unsupervised feature selection and the semi-supervised clustering problem can be usefully formulated as multiobjective optimiz...
Julia Handl, Joshua D. Knowles
IJCNN
2006
IEEE
13 years 10 months ago
C2FS: An Algorithm for Feature Selection in Cascade Neural Networks
Wrapper-based feature selection is attractive because wrapper methods are able to optimize the features they select to the specific learning algorithm. Unfortunately, wrapper met...
Lars Backstrom, Rich Caruana
JCNS
2010
121views more  JCNS 2010»
12 years 11 months ago
Pattern orthogonalization via channel decorrelation by adaptive networks
The early processing of sensory information by neuronal circuits often includes a reshaping of activity patterns that may facilitate the further processing of stimulus representat...
Stuart D. Wick, Martin T. Wiechert, Rainer W. Frie...
ESWA
2006
165views more  ESWA 2006»
13 years 4 months ago
Optimal ensemble construction via meta-evolutionary ensembles
In this paper we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to ...
YongSeog Kim, W. Nick Street, Filippo Menczer
INFORMS
1998
100views more  INFORMS 1998»
13 years 4 months ago
Feature Selection via Mathematical Programming
The problem of discriminating between two nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a...
Paul S. Bradley, Olvi L. Mangasarian, W. Nick Stre...