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A New Boosting Multi-class SVM Algorithm

Author(s): Fereshteh Falah Chamasemani | Yashwant Prasad Singh

Journal: International Journal of Advanced Research in Computer Science
ISSN 0976-5697

Volume: 04;
Issue: 02;
Start page: 01;
Date: 2013;
Original page

Keywords: Boosting | Multi-class | SVM | Multi-class | SVM | Boosting | Algorithm | Boosting | Multi-class | SVM | (BmSVM) | SVM

Support Vector Machines (SVM) have originally designed for binary classification problems. However, Multi-class SVMs (MCSVM)are implemented by combining several binary SVMs. This paper presents a new boosting Multi-class SVMs (BmSVM) to overcomecomputational complexity of existing construction MCSVM methods. The other two objectives of the paper are: first, to show the robustness of BmSVM against different constructing Multi-class SVM methods such as One-Against-All, One-Against-One; Second, to compare theperformance and complexity of BmSVM against SMO, AdaBoost, Decision Tree, and MCSVM. The simulation results demonstrate that theBmSVM on hypothyroid dataset with polynomial kernel is superior to the others.
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