Abstract
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<p>We present a neural network based … <p>We present a neural network based approach for identifying salient features for classification in feedforward neural networks. Our approach involves neural network training with an augmented cross-entropy error function. The augmented error function forces the neural network to keep low derivatives of the transfer functions of neurons when learning a classification task. Such an approach reduces output sensitivity to the input changes. Feature selection is based on the reaction of the cross-validation data set classification error due to the removal of the individual features. We demonstrate the usefulness of the proposed approach on one artificial and three real-world classification problems. We compared the approach with five other feature selection methods, each of which banks on a different concept. The algorithm developed outperformed the other methods by achieving higher classification accuracy on all the problems tested.</p>racy on all the problems tested.</p>
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Author
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Antanas Verikas +
, Marija Bacauskiene +
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DOI
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http://dx.doi.org/10.1016/S0167-8655(02)00081-8 +
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Diva
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http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:235620
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EndPage
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1335 +
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Issue
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11 +
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Journal
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Pattern Recognition Letters +
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PublicationType
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Journal Paper +
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Publisher
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Elsevier +
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StartPage
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1323 +
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Title
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Feature Selection with Neural Networks +
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Volume
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23 +
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Year
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2002 +
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Has queryThis property is a special property in this wiki.
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Publications:Feature Selection with Neural Networks +
, Publications:Feature Selection with Neural Networks +
, Publications:Feature Selection with Neural Networks +
, Publications:Feature Selection with Neural Networks +
, Publications:Feature Selection with Neural Networks +
, Publications:Feature Selection with Neural Networks +
, Publications:Feature Selection with Neural Networks +
, Publications:Feature Selection with Neural Networks +
, Publications:Feature Selection with Neural Networks +
, Publications:Feature Selection with Neural Networks +
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Categories |
Publication +
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Modification dateThis property is a special property in this wiki.
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30 September 2016 20:39:58 +
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