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The Resource An introduction to Support Vector Machines : and other kernel-based learning methods, Nello Cristianini and John Shawe-Taylor

An introduction to Support Vector Machines : and other kernel-based learning methods, Nello Cristianini and John Shawe-Taylor

Label
An introduction to Support Vector Machines : and other kernel-based learning methods
Title
An introduction to Support Vector Machines
Title remainder
and other kernel-based learning methods
Statement of responsibility
Nello Cristianini and John Shawe-Taylor
Creator
Contributor
Subject
Language
eng
Cataloging source
DLC
http://library.link/vocab/creatorName
Cristianini, Nello
Illustrations
illustrations
Index
index present
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
Shawe-Taylor, John
http://library.link/vocab/subjectName
  • Machine learning
  • Algorithms
  • Kernel functions
  • Data mining
  • Machine learning
Label
An introduction to Support Vector Machines : and other kernel-based learning methods, Nello Cristianini and John Shawe-Taylor
Instantiates
Publication
Bibliography note
Includes bibliographical references (p. 173-186) and index
Contents
  • Preface
  • Notation
  • 1.
  • Learning Methodology.
  • p. 1
  • 2.
  • Linear Learning Machines.
  • p. 9
  • 3.
  • Kernel-Induced Feature Spaces.
  • p. 26
  • 4.
  • Generalisation Theory.
  • p. 52
  • 5.
  • Optimisation Theory.
  • p. 79
  • 6.
  • Support Vector Machines.
  • p. 93
  • 7.
  • Implementation Techniques.
  • p. 125
  • 8.
  • Applications of Support Vector Machines.
  • p. 149
  • A.
  • Pseudocode for the SMO Algorithm.
  • p. 162
  • B.
  • Background Mathematics.
  • p. 165
  • References.
  • p. 173
  • Index.
  • p. 187
Control code
090521780195
Dimensions
26 cm.
Edition
Reprint with corrections
Extent
xiii, 189 p
Isbn
9780521780193
Lccn
lc99054716
Other physical details
ill. (some col.)
Label
An introduction to Support Vector Machines : and other kernel-based learning methods, Nello Cristianini and John Shawe-Taylor
Publication
Bibliography note
Includes bibliographical references (p. 173-186) and index
Contents
  • Preface
  • Notation
  • 1.
  • Learning Methodology.
  • p. 1
  • 2.
  • Linear Learning Machines.
  • p. 9
  • 3.
  • Kernel-Induced Feature Spaces.
  • p. 26
  • 4.
  • Generalisation Theory.
  • p. 52
  • 5.
  • Optimisation Theory.
  • p. 79
  • 6.
  • Support Vector Machines.
  • p. 93
  • 7.
  • Implementation Techniques.
  • p. 125
  • 8.
  • Applications of Support Vector Machines.
  • p. 149
  • A.
  • Pseudocode for the SMO Algorithm.
  • p. 162
  • B.
  • Background Mathematics.
  • p. 165
  • References.
  • p. 173
  • Index.
  • p. 187
Control code
090521780195
Dimensions
26 cm.
Edition
Reprint with corrections
Extent
xiii, 189 p
Isbn
9780521780193
Lccn
lc99054716
Other physical details
ill. (some col.)

Library Locations

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      Ashton Street, Liverpool, L69 3DA, GB
      53.418074 -2.967913
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