NDLI: SVM classification for imbalanced data using conformal kernel transformation

Content Provider	IEEE Xplore Digital Library
Author	Yong Zhang Panpan Fu Wenzhe Liu Li Zou
Copyright Year	2014
Description	Author affiliation: Sch. of Comput. & Inf. Technol., Liaoning Normal Univ., Dalian, China (Yong Zhang; Panpan Fu; Wenzhe Liu; Li Zou)
Abstract	The problem of classifying imbalanced datasets has drawn a significant amount of interest from academia and industry. In this paper, we propose a modified support vector machine (SVM) approach using conformal kernel transformation to address the class imbalance problem. The proposed method first uses standard SVM algorithm to obtain an approximate hyperplane. And then, we give a kernel function and compute its parameters using the chi-square test. Finally, an experimental analysis is carried out with a wide range of highly imbalanced datasets over the proposal and several other methods. The results show that our proposal outperforms previously proposed methods.
Starting Page	2894
Ending Page	2900
File Size	3476359
Page Count	7
File Format	PDF
ISSN	21614407
e-ISBN	9781479914845
DOI	10.1109/IJCNN.2014.6889420
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Kernel Classification algorithms Mathematical model Training Equations Measurement conformal kernel transformation support vector machine classification imbalanced data
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
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@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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