Support Vector Machines and Evolutionary Algorithms for Classification

Single or Together?
Softcover Nachdruck of the original 1. Auflage 2014
ISBN: 978-3-319-38243-2
Verlag: Springer

Buch, Englisch, Band 69, 122 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 2234 g

Reihe: Intelligent Systems Reference Library

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 about relying on it, without much understanding of the how and why of its predictions. The question raised in this book is how can this ‘masked hero’ be made more comprehensible and friendly to the public: provide a surrogate model for its hidden optimization engine, replace the method completely or appoint a more friendly approach to tag along and offer the much desired explanations? Evolutionary algorithms can do all these and this book presents such possibilities of achieving high accuracy, comprehensibility, reasonable runtime as well as unconstrained performance.

Zielgruppe

Research

Autoren/Hrsg.

Stoean, Catalin

Stoean, Ruxandra

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

Support Vector Machines.- Evolutionary Algorithms.- Support Vector Machines and Evolutionary Algorithms.