An introduction to support vector machines: and other kernel-based learning methods
This is the first comprehensive introduction to Support Vector Machines (SVMs), a 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,...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2000
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 UER01 Volltext |
| Zusammenfassung: | This is the first comprehensive introduction to Support Vector Machines (SVMs), a 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. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software |
| Beschreibung: | 1 online resource (xiii, 189 pages) |
| ISBN: | 9780511801389 |
| DOI: | 10.1017/CBO9780511801389 |
Internformat
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| 245 | 1 | 0 | |a An introduction to support vector machines |b and other kernel-based learning methods |c Nello Cristianini and John Shawe-Taylor |
| 246 | 1 | 3 | |a An Introduction to Support Vector Machines & Other Kernel-based Learning Methods |
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Datensatz im Suchindex
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| dewey-full | 006.3/1 |
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| dewey-ones | 006 - Special computer methods |
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| dewey-search | 006.3/1 |
| dewey-sort | 16.3 11 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.1017/CBO9780511801389 |
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| id | DE-604.BV043943079 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:19Z |
| institution | BVB |
| isbn | 9780511801389 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029352050 |
| oclc_num | 967777667 |
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| physical | 1 online resource (xiii, 189 pages) |
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| publishDate | 2000 |
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| spelling | Cristianini, Nello 1968- Verfasser (DE-588)133181499 aut An introduction to support vector machines and other kernel-based learning methods Nello Cristianini and John Shawe-Taylor An Introduction to Support Vector Machines & Other Kernel-based Learning Methods Cambridge Cambridge University Press 2000 1 online resource (xiii, 189 pages) txt rdacontent c rdamedia cr rdacarrier This is the first comprehensive introduction to Support Vector Machines (SVMs), a 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. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software ensure that it forms an ideal starting point for further study. Equally, the book and its associated web site will guide practitioners to updated literature, new applications, and on-line software Support vector machines Kernel functions Support-Vektor-Maschine (DE-588)4505517-8 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Lernendes System (DE-588)4120666-6 gnd rswk-swf Lernendes System (DE-588)4120666-6 s Maschinelles Lernen (DE-588)4193754-5 s Support-Vektor-Maschine (DE-588)4505517-8 s 1\p DE-604 Shawe-Taylor, John 1953- Sonstige (DE-588)1151162264 oth Erscheint auch als Druck-Ausgabe 978-0-521-78019-3 https://doi.org/10.1017/CBO9780511801389 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Cristianini, Nello 1968- An introduction to support vector machines and other kernel-based learning methods Support vector machines Kernel functions Support-Vektor-Maschine (DE-588)4505517-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Lernendes System (DE-588)4120666-6 gnd |
| subject_GND | (DE-588)4505517-8 (DE-588)4193754-5 (DE-588)4120666-6 |
| title | An introduction to support vector machines and other kernel-based learning methods |
| title_alt | An Introduction to Support Vector Machines & Other Kernel-based Learning Methods |
| title_auth | An introduction to support vector machines and other kernel-based learning methods |
| title_exact_search | An introduction to support vector machines and other kernel-based learning methods |
| title_full | An introduction to support vector machines and other kernel-based learning methods Nello Cristianini and John Shawe-Taylor |
| title_fullStr | An introduction to support vector machines and other kernel-based learning methods Nello Cristianini and John Shawe-Taylor |
| title_full_unstemmed | An introduction to support vector machines and other kernel-based learning methods Nello Cristianini and John Shawe-Taylor |
| title_short | An introduction to support vector machines |
| title_sort | an introduction to support vector machines and other kernel based learning methods |
| title_sub | and other kernel-based learning methods |
| topic | Support vector machines Kernel functions Support-Vektor-Maschine (DE-588)4505517-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Lernendes System (DE-588)4120666-6 gnd |
| topic_facet | Support vector machines Kernel functions Support-Vektor-Maschine Maschinelles Lernen Lernendes System |
| url | https://doi.org/10.1017/CBO9780511801389 |
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