ENGLISH

Support Vector Machines and Evolutionary Algorithms for Classification: Single or Together?

By Catalin Stoean , Ruxandra Stoean (auth.)

Book information

Publisher
Springer International Publishing
Year
2014
ISBN
978-3-319-06940-1, 978-3-319-06941-8
DOI
10.1007/978-3-319-06941-8
Language
english
Format
PDF
Filesize
3 MB (2681297 bytes)
Series
Intelligent Systems Reference Library 69
Edition
1
Pages
122\129
Time added
2014-06-12 06:00:00
Computational Intelligence; Artificial Intelligenc

Description

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.

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