Electronic Resource

Support Vector Machines and Evolutionary Algorithms for Classification: ingle or Together

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Penilaian

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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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Availability

Inventory Code	Barcode	Call Number	Location	Status
1408000280	EB0000488	518.1 Sto s	Central Library	Available

Detail Information

Series Title

Intelligent Systems Reference Library

Call Number

518.1 Sto s

Publisher

Switzerland : Springer Cham., 2014

Collation

xvi, 122p.: III.

Language

English

ISBN/ISSN

978-3-319-06941-8

Classification

518.1

Content Type

-

Media Type

-

Carrier Type

-

Edition

1

Subject(s)

Support vector machines

Specific Detail Info

-

Statement of Responsibility

RIZAL

Other version/related

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