NDLI: Input selection by multilayer feedforward trained networks

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Input selection by multilayer feedforward trained networks

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Input selection by multilayer feedforward trained networks

Content Provider	IEEE Xplore Digital Library
Author	Redondo, M.F. Espinosa, C.H.
Copyright Year	1999
Description	Author affiliation: Dept. de Inf., Univ. James I, Castellon, Spain (Redondo, M.F.)
Abstract	We review feature selection methods based on the analysis of a trained multilayer feedforward neural network. Furthermore, we present a methodology that allows experimentally evaluating and comparing feature selection methods. This methodology was applied to the 19 reviewed methods and we evaluated the usefulness of these methods for selecting the appropriate features in the case of using a multilayer feedforward as a pattern recognition method. We used a total number of 15 different real world classification problems in our experiments. From the result of the comparison, we conclude which methods perform better and should be used, and discuss their applicability.
Starting Page	1834
Ending Page	1839
File Size	486364
Page Count	6
File Format	PDF
ISBN	0780355296
ISSN	10987576
DOI	10.1109/IJCNN.1999.832658
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-07-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nonhomogeneous media Neural networks Multi-layer neural network Pattern recognition Performance analysis Feedforward neural networks Algorithm design and analysis Medical diagnosis Bibliographies Genetic algorithms
Content Type	Text
Resource Type	Article

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