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2005
ACM

A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data

10 years 9 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a network pruning algorithm acting on MultiLayer Perceptron topology is the foundation of the feature selection strategy. Feature selection is implemented within the back-propagation learning process and based on a measure of saliency derived from bell functions positioned between input and hidden layers and adaptively varied in shape and position during learning. Performances were evaluated experimentally within a Remote Sensing study, aimed to classify hyperspectral data. A comparison analysis was conducted with Support Vector Machine and conventional statistical and neural techniques. As seen in the experimental context, the adaptive neural classifier showed a competitive behavior with respect to the other classifiers considered; it performed a selection of the most relevant features and showed a robust behavi...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti
Added 08 Dec 2009
Updated 08 Dec 2009
Type Conference
Year 2005
Where ICIAP
Authors Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti, Pietro Alessandro Brivio
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