Support Vector Machines

Jaime Gòmez Sàenz de Tejada and Juan Seijas Martìnez-Echevarrìa
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Jaime Gòmez Sàenz de Tejada: Universidad Auònoma de Madrid, Escuela Politècnica Superior
Juan Seijas Martìnez-Echevarrìa: Universidad Politècnica de Madrid, Escuela Tècnica ,Superior de Ingenieros de Telecomunicaciones

Chapter Chapter 7 in Computational Intelligence, 2007, pp 147-191 from Springer

Abstract: Support Vector Machines is the most recent algorithm in the Machine Learning community. After a bit less than a decade of live, it has displayed many advantages with respect to the best old methods: generalization capacity, ease of use, solution uniqueness. It has also shown some disadvantages: maximum data handling and speed in the training phase. However, these disadvantages will be overcome in the near future, as computer power increases, leaving an all-purpose learning method both cheap to use and giving the best performance. This chapter provides an overview about the main SVM configuration, its mathematical applications and the easiest implementation

Keywords: Support Vector Machines; Machine Learning (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/0-387-37452-3_7

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