Feature selection: evaluation, application, and small sampleperformance
Jain, A.
Zongker, D.
Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Feb 1997
Volume: 19,
Issue: 2
On page(s): 153-158
ISSN: 0162-8828
References Cited: 19
CODEN: ITPIDJ
INSPEC Accession Number: 5529628
Digital Object Identifier: 10.1109/34.574797
Current Version Published: 2002-08-06
Abstract
A large number of algorithms have been proposed for feature subset
selection. Our experimental results show that the sequential forward
floating selection algorithm, proposed by Pudil et al. (1994), dominates
the other algorithms tested. We study the problem of choosing an optimal
feature set for land use classification based on SAR satellite images
using four different texture models. Pooling features derived from
different texture models, followed by a feature selection results in a
substantial improvement in the classification accuracy. We also
illustrate the dangers of using feature selection in small sample size
situations
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