An Output Grouping Based Approach to Multiclass Classification Using Support Vector Machines
Support Vector Machine (SVM) classifiers are binary classifiers in nature, which have to be coupled/assembled to solve multi-class problems. One-Versus-Rest (1-v-r) is a fast and accurate method for SVM multiclass classification. This paper investigates t
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James J. (Jong Hyuk) Park Hai Jin Young-Sik Jeong Muhammad Khurram Khan Editors
Advanced Multimedia and Ubiquitous Engineering FutureTech & MUE
Lecture Notes in Electrical Engineering Volume 393
Board of Series editors Leopoldo Angrisani, Napoli, Italy Marco Arteaga, Coyoacán, México Samarjit Chakraborty, München, Germany Jiming Chen, Hangzhou, P.R. China Tan Kay Chen, Singapore, Singapore Rüdiger Dillmann, Karlsruhe, Germany Haibin Duan, Beijing, China Gianluigi Ferrari, Parma, Italy Manuel Ferre, Madrid, Spain Sandra Hirche, München, Germany Faryar Jabbari, Irvine, USA Janusz Kacprzyk, Warsaw, Poland Alaa Khamis, New Cairo City, Egypt Torsten Kroeger, Stanford, USA Tan Cher Ming, Singapore, Singapore Wolfgang Minker, Ulm, Germany Pradeep Misra, Dayton, USA Sebastian Möller, Berlin, Germany Subhas Mukhopadyay, Palmerston, New Zealand Cun-Zheng Ning, Tempe, USA Toyoaki Nishida, Sakyo-ku, Japan Bijaya Ketan Panigrahi, New Delhi, India Federica Pascucci, Roma, Italy Tariq Samad, Minneapolis, USA Gan Woon Seng, Nanyang Avenue, Singapore Germano Veiga, Porto, Portugal Haitao Wu, Beijing, China Junjie James Zhang, Charlotte, USA
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James J. (Jong Hyuk) Park Hai Jin Young-Sik Jeong Muhammad Khurram Khan •
Editors
Advanced Multimedia and Ubiquitous Engineering FutureTech & MUE
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Editors James J. (Jong Hyuk) Park Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul Korea (Republic of) Hai Jin School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China
Young-Sik Jeong Department of Multimedia Engineering Dongguk University Seoul Korea (Republic of) Muhammad Khurram Khan College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia
ISSN 1876-1100 ISSN 1876-1119 (electronic) Lecture Notes in Electrical Engineering ISBN 978
