Selecting optimal experiments for multiple output multilayer perceptrons
Neural Computation
Feature selection with neural networks
Pattern Recognition Letters
Feature Extraction Based on ICA for Binary Classification Problems
IEEE Transactions on Knowledge and Data Engineering
Selecting salient features for classification based on neural network committees
Pattern Recognition Letters
On fuzzy-rough sets approach to feature selection
Pattern Recognition Letters
Predictor output sensitivity and feature similarity-based feature selection
Fuzzy Sets and Systems
Modeling consumer situational choice of long distance communication with neural networks
Decision Support Systems
Combined input variable selection and model complexity control for nonlinear regression
Pattern Recognition Letters
Engineering Applications of Artificial Intelligence
Expert Systems with Applications: An International Journal
A predication survival model for colorectal cancer
AMERICAN-MATH'11/CEA'11 Proceedings of the 2011 American conference on applied mathematics and the 5th WSEAS international conference on Computer engineering and applications
Engineering Applications of Artificial Intelligence
Feature subset selection wrapper based on mutual information and rough sets
Expert Systems with Applications: An International Journal
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In this paper, we present an integrated approach to feature and architecture selection for single hidden layer-feedforward neural networks trained via backpropagation. In our approach, we adopt a statistical model building perspective in which we analyze neural networks within a nonlinear regression framework. The algorithm presented in this paper employs a likelihood-ratio test statistic as a model selection criterion. This criterion is used in a sequential procedure aimed at selecting the best neural network given an initial architecture as determined by heuristic rules. Application results for an object recognition problem demonstrate the selection algorithm's effectiveness in identifying reduced neural networks with equivalent prediction accuracy