NDLI: Identification of feature-salience

Content Provider	IEEE Xplore Digital Library
Author	Wang, W. Jones, P. Partridge, D.
Copyright Year	2000
Description	Author affiliation: Dept. of Comput. Sci., Exeter Univ., UK (Wang, W.)
Abstract	In this paper we present two techniques designed to identify the relative salience of features in a data-defined problem with respect to their ability to predict a category outcome-e.g., which features of a character contribute most to accurate prediction of outcome. The first technique we proposed is a neural-net based clamping technique and another is based on inductive learning algorithm-decision tree's heuristic. They are compared with a number of other techniques, i.e., automatic relevance determination (ARD), weight-product, random selection, in addition to a standard statistical technique-linear correlation analysis. The salience of the features that compose a proposed set is an important problem to solve efficiently and effectively not only for neural computing technology but also in order to provide a sound basis for any attempt to design an optimal computational system. The focus of this study is the efficiency as well as the effectiveness with which high-salience subsets of features can be identified in the context of ill-understood and potentially noisy real-world data.
Starting Page	559
Ending Page	564
File Size	491469
Page Count	6
File Format	PDF
ISBN	0769506194
ISSN	10987576
DOI	10.1109/IJCNN.2000.861528
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-07-27
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clamps Neural networks Data mining Decision trees Costs Computer science Acoustic noise Feature extraction Computer networks Production
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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