NDLI: Binary Classification Based on Potentials

Content Provider	IEEE Xplore Digital Library
Author	Boczko, E.M. Di Lullo, A. Young, T.R.
Copyright Year	2009
Abstract	We introduce a simple and computationally trivial method for binary classification based on the evaluation of potential functions. We demonstrate that despite the conceptual and computational simplicity of the method its performance can match or exceed that of standard SupportVector Machine methods.
Starting Page	129
Ending Page	132
File Size	253875
Page Count	4
File Format	PDF
ISBN	9780769536859
DOI	10.1109/OCCBIO.2009.31
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Microarray Data Support vector machine classification Biomedical informatics Collaboration Machine learning Proteomics Biomedical computing Mathematics Bioinformatics Joining processes Machine Learning
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
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Binary Classification Based on Potentials