NDLI: Kernel Classifier Construction Using Orthogonal Forward Selection and Boosting With Fisher Ratio Class Separability Measure

Content Provider	IEEE Xplore Digital Library
Author	Chen, S. Wang, X.X. Hong, X. Harris, C.J.
Copyright Year	1990
Abstract	A greedy technique is proposed to construct parsimonious kernel classifiers using the orthogonal forward selection method and boosting based on Fisher ratio for class separability measure. Unlike most kernel classification methods, which restrict kernel means to the training input data and use a fixed common variance for all the kernel terms, the proposed technique can tune both the mean vector and diagonal covariance matrix of individual kernel by incrementally maximizing Fisher ratio for class separability measure. An efficient weighted optimization method is developed based on boosting to append kernels one by one in an orthogonal forward selection procedure. Experimental results obtained using this construction technique demonstrate that it offers a viable alternative to the existing state-of-the-art kernel modeling methods for constructing sparse Gaussian radial basis function network classifiers that generalize well
Sponsorship	IEEE Computational Intelligence Society
Page Count	5
File Size	266780
Starting Page	1652
Ending Page	1656
File Format	PDF
ISSN	10459227
Volume Number	17
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Boosting Covariance matrix Radial basis function networks Training data Support vector machines Support vector machine classification Optimization methods Least squares methods Robustness radial basis function network classification Fisher ratio of class separability forward selection kernel classifier orthogonal least square
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Computer Science Applications Software

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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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