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» CB3: An Adaptive Error Function for Backpropagation Training
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ESANN
1997
13 years 6 months ago
Extraction of crisp logical rules using constrained backpropagation networks
Two recently developed methods for extraction of crisp logical rules from neural networks trained with backpropagation algorithm are compared. Both methods impose constraints on th...
Wlodzislaw Duch, Rafal Adamczak, Krzysztof Grabcze...
ML
2006
ACM
110views Machine Learning» more  ML 2006»
13 years 5 months ago
Classification-based objective functions
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Michael Rimer, Tony Martinez
PR
2006
111views more  PR 2006»
13 years 5 months ago
An adaptive error penalization method for training an efficient and generalized SVM
A novel training method has been proposed for increasing efficiency and generalization of support vector machine (SVM). The efficiency of SVM in classification is directly determi...
Yiqiang Zhan, Dinggang Shen
TNN
2010
176views Management» more  TNN 2010»
12 years 12 months ago
On the weight convergence of Elman networks
Abstract--An Elman network (EN) can be viewed as a feedforward (FF) neural network with an additional set of inputs from the context layer (feedback from the hidden layer). Therefo...
Qing Song
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
13 years 8 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic