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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 5/2016

01.10.2016 | Original Article

Multiple recursive projection twin support vector machine for multi-class classification

verfasst von: Chun-Na Li, Yun-Feng Huang, He-Ji Wu, Yuan-Hai Shao, Zhi-Min Yang

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 5/2016

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Abstract

For multi-class classification problem, a novel multiple projection twin support vector machine (Multi-PTSVM) is proposed. Our Multi-PTSVM solves \(K\) quadratic programming problems (QPPs) to obtain \(K\) projection axes, which is similar to binary PTSVM, but the regularization terms and recursive procedure are introduced for each class, which improve the generalization ability greatly. Comparisons against the Multi-SVM, Multi-TWSVM, Multi-GEPSVM, and our Multi-PTSVM on both synthetic and benchmark datasets indicate that our Multi-PTSVM has its advantages.
Vorheriger Artikel On optimization based extreme learning machine in primal for regression and classification by functional iterative method
Nächster Artikel Speeding up maximal fully-correlated itemsets search in large databases

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Metadaten
Titel
Multiple recursive projection twin support vector machine for multi-class classification
verfasst von
Chun-Na Li
Yun-Feng Huang
He-Ji Wu
Yuan-Hai Shao
Zhi-Min Yang
Publikationsdatum
01.10.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 5/2016
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-014-0289-2

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