FEATURE ANALYSIS - NEURAL-NETWORK AND FUZZY SET-THEORETIC APPROACHES

Authors
DE RK PAL NR PAL SK
Citation
Rk. De et al., FEATURE ANALYSIS - NEURAL-NETWORK AND FUZZY SET-THEORETIC APPROACHES, Pattern recognition, 30(10), 1997, pp. 1579-1590
Citations number
17
Categorie Soggetti
Computer Sciences, Special Topics","Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence
Journal title
Pattern recognition → ACNP
ISSN journal
00313203
Volume
30
Issue
10
Year of publication
1997
Pages
1579 - 1590
Database
ISI
SICI code
0031-3203(1997)30:10<1579:FA-NAF>2.0.ZU;2-S
Abstract
In this paper a new scheme of feature ranking and hence feature select ion using a Multilayer Perceptron (MLP) Network has been proposed. The novelty of the proposed MLP-based scheme and its difference from anot her MLP-based feature ranking scheme have been analyzed. In addition w e have modified an existing feature ranking/selection scheme based on fuzzy entropy. Empirical investigations show that the proposed MLP-bas ed scheme is superior to the other schemes implemented. (C) 1997 Patte rn Recognition Society. Published by Elsevier Science Ltd.