NDLI: Cost-Constrained Feature Optimization in Kernel Machine Classifiers

Content Provider	IEEE Xplore Digital Library
Author	Ratto, C.R. Caceres, C.A. Schoeberlein, H.C.
Copyright Year	1994
Abstract	Feature selection is often necessary when implementing classifiers in practice. Most approaches to feature selection are motivated by the curse of dimensionality, but few seek to mitigate the overall computational cost of feature extraction. In this work, we propose a model-based approach for addressing both objectives. The model is based around a sparse kernel machine with feature scaling parameters controlled by a beta-Bernoulli prior. The hyperparameters are controlled by each feature's computational cost. Experiments were carried out using publicly-available data sets, and the proposed Cost-Constrained Feature Optimization (CCFO) was compared to related methods in terms of accuracy and computational reduction.
Sponsorship	IEEE Signal Processing Society
Starting Page	2469
Ending Page	2473
Page Count	5
File Size	898239
File Format	PDF
ISSN	10709908
Volume Number	22
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Kernel Computational efficiency Expectation-maximization algorithms Pattern classification sparse kernel machine Bayesian machine learning beta process expectation-maximization model-based feature selection multispectral remote sensing pattern classification
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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