NDLI: An Experimental Study on Number of Support Vectors in N-bit Parity Problem

Content Provider	IEEE Xplore Digital Library
Author	Xun Liang
Copyright Year	2010
Abstract	Support vector machine (SV machine, SVM) is a genius invention with many merits, such as the non-existence of local minima, the largest separating margins of different clusters, as well as the solid theoretical foundation. However, it is also well-noted that SVMs are frequently with a large number of SVs. In this paper, we investigate the number of SVs in a benchmark problem, the parity problem experimentally. With a large variety of kernel functions, the exhaustive experiments using LibSVM discover that for the N-bit parity problems all 2N points are created as SVs. The study in this paper indicates that the SMO-based LibSVM training candidly incorporate every point in the parity problem. Since any two neighbored points in the N-bit parity problem are with the opposite signs, the SMO creates an SV each time in iterations for fast satisfying the Lagrangian conditions. As a corollary, the SMO-based SVM training is pretty much entangled into the local information and is therefore a greedy algorithm.
Starting Page	1
Ending Page	4
File Size	232689
Page Count	4
File Format	PDF
ISBN	9781424453917
DOI	10.1109/CISE.2010.5677041
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Training Google Artificial neural networks Kernel Optimization
Content Type	Text
Resource Type	Article

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

Reducing neural network training data using support vectors

Support vector machines versus artificial neural networks in data classification

Identifying uncertainty regions in Support Vector Machines using geometric margin and convex hulls

An application of support vector machines for image retrieval

Friction modelling based on support vector regression machines and genetic algorithms

Application of Support Vector Machines in Financial Literacy Modelling

A Study on Combining Sets of Differently Measured Dissimilarities

An efficient finite precision RBF-M neural network architecture using support vectors

RBF Neural Networks Optimization Algorithm Based on Support Vector Machine and Its Application

An Experimental Study on Number of Support Vectors in N-bit Parity Problem

Similar Documents

Reducing neural network training data using support vectors

Support vector machines versus artificial neural networks in data classification

Identifying uncertainty regions in Support Vector Machines using geometric margin and convex hulls

An application of support vector machines for image retrieval

Friction modelling based on support vector regression machines and genetic algorithms

Application of Support Vector Machines in Financial Literacy Modelling

A Study on Combining Sets of Differently Measured Dissimilarities

An efficient finite precision RBF-M neural network architecture using support vectors

RBF Neural Networks Optimization Algorithm Based on Support Vector Machine and Its Application

An Experimental Study on Number of Support Vectors in N-bit Parity Problem