Title :
Proving to the Coincidence of the Solutions of the Modified Problem with the Original Problem of Multi-class Support Vector Machine
Author :
Xue, Xin ; He, Guoping ; Zhao, Chenglong
Author_Institution :
Coll. of Inf. Sci. & Eng., Shandong Univ. of Sci. & Technol., Qingdao
Abstract :
Vojtech Franc and Vaclav Hlavac proposed a transformation from the multi-class support vector machine problem to the one-class support vector machine problem which is more convenient for optimization. Moreover, the proposed transformation can be performed by the properly defined kernel function only. The experiments conducted indicate that the proposed method is comparable with the one-against-all decomposition solved by the state-of-the-art sequential minimal optimizer algorithms. This paper proves strictly with theory that the solution of the one-class support vector machine problem coincides mostly with the solution of the multi-class support vector machine problem.
Keywords :
optimisation; support vector machines; kernel function; multiclass support vector machine; one-against-all decomposition; optimization; sequential minimal optimizer algorithms; Cost function; Educational institutions; Fuzzy systems; Information science; Kernel; Knowledge engineering; Machine learning algorithms; Optimization methods; Support vector machine classification; Support vector machines; Coincidence; Multi-class Support Vector Machine; One-class Support Vector Machine; Solution;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Shandong
Print_ISBN :
978-0-7695-3305-6
DOI :
10.1109/FSKD.2008.196