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» Training a Selection Function for Extraction
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MSV
2007
13 years 9 months ago
Assessment of ARMAX Structure as a Global Model for Self-Refilling Steam Distillation Essential Oil Extraction System
Abstract - In this paper, an essential oil extraction system with self-refilling system is modeled based on inputoutput data collected from a dedicated acquisition system. The ARMA...
Mohd Hezri Fazalul Rahiman, Mohd Nasir Taib, Yusof...
NN
2008
Springer
143views Neural Networks» more  NN 2008»
13 years 7 months ago
A batch ensemble approach to active learning with model selection
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
CIKM
2011
Springer
12 years 7 months ago
Toward interactive training and evaluation
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
Gregory Druck, Andrew McCallum
IJCNN
2007
IEEE
14 years 1 months ago
A Functional Link Network With Ordered Basis Functions
—A procedure is presented for selecting and ordering the polynomial basis functions in the functional link net (FLN). This procedure, based upon a modified Gram Schmidt orthonorm...
Saurabh Sureka, Michael T. Manry