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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Buch von John Shawe-Taylor
Sprache: Englisch

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Beschreibung
This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications.
This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications.
Inhaltsverzeichnis
Preface; 1. The learning methodology; 2. Linear learning machines; 3. Kernel-induced feature spaces; 4. Generalisation theory; 5. Optimisation theory; 6. Support vector machines; 7. Implementation techniques; 8. Applications of support vector machines; Appendix A: pseudocode for the SMO algorithm; Appendix B: background mathematics; Appendix C: glossary; Appendix D: notation; Bibliography; Index.
Details
Erscheinungsjahr: 2015
Fachbereich: EDV
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 204
ISBN-13: 9780521780193
ISBN-10: 0521780195
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Shawe-Taylor, John
Hersteller: Cambridge University Press
Maße: 250 x 175 x 16 mm
Von/Mit: John Shawe-Taylor
Erscheinungsdatum: 07.01.2015
Gewicht: 0,542 kg
preigu-id: 106200385
Inhaltsverzeichnis
Preface; 1. The learning methodology; 2. Linear learning machines; 3. Kernel-induced feature spaces; 4. Generalisation theory; 5. Optimisation theory; 6. Support vector machines; 7. Implementation techniques; 8. Applications of support vector machines; Appendix A: pseudocode for the SMO algorithm; Appendix B: background mathematics; Appendix C: glossary; Appendix D: notation; Bibliography; Index.
Details
Erscheinungsjahr: 2015
Fachbereich: EDV
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 204
ISBN-13: 9780521780193
ISBN-10: 0521780195
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Shawe-Taylor, John
Hersteller: Cambridge University Press
Maße: 250 x 175 x 16 mm
Von/Mit: John Shawe-Taylor
Erscheinungsdatum: 07.01.2015
Gewicht: 0,542 kg
preigu-id: 106200385
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