NDLI: Adaptation of Gaussian ARD kernel for multiclass classification

Content Provider	IEEE Xplore Digital Library
Author	Tinghua Wang
Copyright Year	2011
Description	Author affiliation: School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China (Tinghua Wang)
Abstract	The problem of optimizing Gaussian Automatic Relevance (ARD) kernel in a multiclass setting is considered. Unlike the conventional Gaussian kernel with a single width parameter, the Gaussian ARD kernel adopts multiple widths corresponding to the input features. We first present a model selection criterion named kernel distance-based class separability (KDCS) to evaluate the goodness of a kernel in multiclass classification scenario, then propose a gradient-based optimization algorithm to tune the width parameters of Gaussian ARD kernel via maximizing the KDCS criterion. This method is essentially a feature weighting method since each learned parameter indicates the relative importance of the corresponding feature. The proposed method is demonstrated with some UCI machine learning benchmark examples.
Starting Page	983
Ending Page	986
File Size	246633
Page Count	4
File Format	PDF
ISBN	9781612841809
e-ISBN	9781612841816
DOI	10.1109/FSKD.2011.6019661
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training auto relevance determination (ARD) multiclass classification Support vector machine classification Machine learning model selection feature weighting Kernel Optimization Ionosphere support vector machines (SVMs)
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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