Rule Extraction from Support Vector Machines (Record no. 21513)

MARC details
000 -LEADER
fixed length control field 03817nam a22004695i 4500
001 - CONTROL NUMBER
control field 978-3-540-75390-2
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20170628034803.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 100301s2008 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783540753902
-- 978-3-540-75390-2
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-540-75390-2
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA329-348
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA640-643
072 #7 - SUBJECT CATEGORY CODE
Subject category code TBJ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT003000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Diederich, Joachim.
Relator term editor.
245 10 - TITLE STATEMENT
Title Rule Extraction from Support Vector Machines
Medium [electronic resource] /
Statement of responsibility, etc edited by Joachim Diederich.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg,
-- 2008.
300 ## - PHYSICAL DESCRIPTION
Extent XII, 262 p. 55 illus.
Other physical details online resource.
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-- text
-- txt
-- rdacontent
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-- computer
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-- rdamedia
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-- online resource
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347 ## -
-- text file
-- PDF
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490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
International Standard Serial Number 1860-949X ;
Volume number/sequential designation 80
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Rule Extraction from Support Vector Machines: An Introduction -- Rule Extraction from Support Vector Machines: An Overview of Issues and Application in Credit Scoring -- Algorithms and Techniques -- Rule Extraction for Transfer Learning -- Rule Extraction from Linear Support Vector Machines via Mathematical Programming -- Rule Extraction Based on Support and Prototype Vectors -- SVMT-Rule: Association Rule Mining Over SVM Classification Trees -- Prototype Rules from SVM -- Applications -- Prediction of First-Day Returns of Initial Public Offering in the US Stock Market Using Rule Extraction from Support Vector Machines -- Accent in Speech Samples: Support Vector Machines for Classification and Rule Extraction -- Rule Extraction from SVM for Protein Structure Prediction.
520 ## - SUMMARY, ETC.
Summary, etc 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering mathematics.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Appl.Mathematics/Computational Methods of Engineering.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783540753896
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Studies in Computational Intelligence,
-- 1860-949X ;
Volume number/sequential designation 80
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://dx.doi.org/10.1007/978-3-540-75390-2">http://dx.doi.org/10.1007/978-3-540-75390-2</a>
912 ## -
-- ZDB-2-ENG
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Total Checkouts Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Central Library Central Library 28/06/2017 Springer EBook   E-44692 28/06/2017 28/06/2017 E-Book

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