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» On learning algorithm selection for classification
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TNN
2010
176views Management» more  TNN 2010»
13 years 3 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
IJIT
2004
13 years 10 months ago
Genetic Algorithm for Feature Subset Selection with Exploitation of Feature Correlations from Continuous Wavelet Transform: a re
A genetic algorithm (GA) based feature subset selection algorithm is proposed in which the correlation structure of the features is exploited. The subset of features is validated a...
Gert Van Dijck, Marc M. Van Hulle, M. Wevers
ESANN
2006
13 years 10 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
BMCBI
2008
170views more  BMCBI 2008»
13 years 9 months ago
A genetic approach for building different alphabets for peptide and protein classification
Background: In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task i...
Loris Nanni, Alessandra Lumini
CVPR
2006
IEEE
14 years 10 months ago
Supervised Learning of Edges and Object Boundaries
Edge detection is one of the most studied problems in computer vision, yet it remains a very challenging task. It is difficult since often the decision for an edge cannot be made ...
Piotr Dollár, Zhuowen Tu, Serge Belongie