Rule Extraction from Support Vector Machines: 80 (Studies in Computational Intelligence, 80) - Tapa dura

 
9783540753896: Rule Extraction from Support Vector Machines: 80 (Studies in Computational Intelligence, 80)
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ISBN 10: 3540753893 ISBN 13: 9783540753896
Editorial: Springer, 2008

Sinopsis

Overa period spanning morethana decade,supportvector machines (SVMs) have evolved into a leading machine learning technique. SVMs are being applied to a wide range of problems, including bioinformatics, face rec- nition, text classi?cation and many more. It is fair to say that SVMs are one of the most important methods used for data mining with a wide range of software available to support their application. A signi?cant barrier to the widespread application of support vector machines is the absence of a capability to explain, in a human comprehensible form,either the process by which anSVM arrivesat a speci?c decision/result, or more general, the totality of knowledge embedded in these systems. This lack of a capacity to provide an explanation is an obstacle to a more g- eral acceptance of "back box" machine learning systems. In safety-critical or medical applications, an explanation capability is an absolute requirement. This book provides an introduction and overviewof methods used for rule extractionfrom support vector machines.The ?rst parto?ers an introduction to the topic as well as a summary of current research issues. The second chaptersurveysthe?eldofruleextractionfromSVMs,reviewsareasofcurrent research and introduces an application in the ?nancial ?eld.

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De la contraportada

Support vector machines (SVMs) are one of the most active research areas in machine learning. SVMs have shown good performance in a number of applications, including text and image classification. However, the learning capability of SVMs comes at a cost – an inherent inability to explain in a comprehensible form, the process by which a learning result was reached. Hence, the situation is similar to neural networks, where the apparent lack of an explanation capability has led to various approaches aiming at extracting symbolic rules from neural networks. For SVMs to gain a wider degree of acceptance in fields such as medical diagnosis and security sensitive areas, it is desirable to offer an explanation capability. User explanation is often a legal requirement, because it is necessary to explain how a decision was reached or why it was made.

This book provides an overview of the field and introduces a number of different approaches to extracting rules from support vector machines developed by key researchers. In addition, successful applications are outlined and future research opportunities are discussed. The book is an important reference for researchers and graduate students, and since it provides an introduction to the topic, it will be important in the classroom as well. Because of the significance of both SVMs and user explanation, the book is of relevance to data mining practitioners and data analysts.

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Editorial
Springer
Año de publicación
2008
Idioma
Inglés
ISBN 10 
3540753893
ISBN 13 
9783540753896
Encuadernación
Tapa dura
Número de páginas
276
Editor
Diederich Joachim
Contacto del fabricante
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Alemania

Otras ediciones populares con el mismo título

9783642094637: Rule Extraction from Support Vector Machines: 80 (Studies in Computational Intelligence)

Edición Destacada

ISBN 10:  3642094635 ISBN 13:  9783642094637
Editorial: Springer, 2010
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