Support Vector Machines and Evolutionary Algorithms for Classification
When discussing classification, support vector machines are known to be a capable and efficient technique to learn and predict with high accuracy within a quick time frame. Yet, their black box means to do so make the practical users quite circumspect abo
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Catalin Stoean Ruxandra Stoean
Support Vector Machines and Evolutionary Algorithms for Classification Single or Together?
Intelligent Systems Reference Library Volume 69
Series editors Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected] Lakhmi C. Jain, University of Canberra, Canberra, Australia e-mail: [email protected]
For further volumes: http://www.springer.com/series/8578
About this Series The aim of this series is to publish a Reference Library, including novel advances and developments in all aspects of Intelligent Systems in an easily accessible and well structured form. The series includes reference works, handbooks, compendia, textbooks, well-structured monographs, dictionaries, and encyclopedias. It contains well integrated knowledge and current information in the field of Intelligent Systems. The series covers the theory, applications, and design methods of Intelligent Systems. Virtually all disciplines such as engineering, computer science, avionics, business, e-commerce, environment, healthcare, physics and life science are included.
Catalin Stoean · Ruxandra Stoean
Support Vector Machines and Evolutionary Algorithms for Classification Single or Together?
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Catalin Stoean Faculty of Mathematics and Natural Sciences Department of Computer Science University of Craiova Craiova Romania
ISSN 1868-4394 ISBN 978-3-319-06940-1 DOI 10.1007/978-3-319-06941-8
Ruxandra Stoean Faculty of Mathematics and Natural Sciences Department of Computer Science University of Craiova Craiova Romania
ISSN 1868-4408 (electronic) ISBN 978-3-319-06941-8 (eBook)
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