Comments on: Support vector machines maximizing geometric margins for multi-class classification 1

• Shigeo Abe ^[1]
  1. [1] Kobe University

     Kobe University

     Chuo-ku, Japón

     
• Localización: Top, ISSN-e 1863-8279, ISSN 1134-5764, Vol. 22, Nº. 3, 2014, págs. 841-843
• Idioma: inglés
• DOI: 10.1007/s11750-014-0339-7
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• Resumen

  • The support vector machine (SVM) is one of the most popular classification algorithms. In the SVM, the minimum distance from the separating hyperplane to training samples of one class is called margin and the SVM is trained so that the margin is maximized under the constraint that the margin of one class is the same as that of the other. (The resulting separating hyperplane is called optimal separating hyperplane.)