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 recogni...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge ; New York :
Cambridge University Press,
[2000]
|
| Schlagworte: | |
| Online-Zugang: | 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."--Provided by publisher. |
| Beschreibung: | 1 online resource (xiii, 189 pages) : illustrations (some color) |
| Bibliographie: | Includes bibliographical references (pages 173-186) and index. |
| ISBN: | 9781139649087 1139649086 9780511801389 0511801386 9781139638623 1139638629 1316085414 9781316085417 1139641468 9781139641463 |
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| 100 | 1 | |a Cristianini, Nello, |e author. |0 http://id.loc.gov/authorities/names/nb99092565 | |
| 245 | 1 | 3 | |a An introduction to support vector machines : |b and other kernel-based learning methods / |c Nello Cristianini and John Shawe-Taylor. |
| 264 | 1 | |a Cambridge ; |a New York : |b Cambridge University Press, |c [2000] | |
| 300 | |a 1 online resource (xiii, 189 pages) : |b illustrations (some color) | ||
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| 504 | |a Includes bibliographical references (pages 173-186) and index. | ||
| 505 | 0 | |a The learning methodology -- Linear learning machines -- Kernal-induced feature spaces -- Generalisation theory -- Optimisation theory -- Support vector machines -- Implementation techniques -- Application of support vector machines -- Pseudocode for the SMO algorithm -- Background mathematics. | |
| 588 | 0 | |a Description based on online resource; title from digital title page (Cambridge, viewed on June 5, 2024). | |
| 520 | |a "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."--Provided by publisher. | ||
| 546 | |a English. | ||
| 650 | 0 | |a Support vector machines. |0 http://id.loc.gov/authorities/subjects/sh2008009003 | |
| 650 | 0 | |a Kernel functions. |0 http://id.loc.gov/authorities/subjects/sh85072061 | |
| 650 | 0 | |a Machine learning. |0 http://id.loc.gov/authorities/subjects/sh85079324 | |
| 650 | 0 | |a Computer algorithms. |0 http://id.loc.gov/authorities/subjects/sh91000149 | |
| 650 | 0 | |a Algorithms. |0 http://id.loc.gov/authorities/subjects/sh85003487 | |
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| author | Cristianini, Nello Shawe-Taylor, John |
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| genre | Electronic book. |
| genre_facet | Electronic book. |
| id | ZDB-4-EBU-ocn852896272 |
| illustrated | Illustrated |
| indexdate | 2024-11-26T14:49:10Z |
| institution | BVB |
| isbn | 9781139649087 1139649086 9780511801389 0511801386 9781139638623 1139638629 1316085414 9781316085417 1139641468 9781139641463 |
| language | English |
| oclc_num | 852896272 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (xiii, 189 pages) : illustrations (some color) |
| psigel | ZDB-4-EBU |
| publishDate | 2000 |
| publishDateSearch | 2000 |
| publishDateSort | 2000 |
| publisher | Cambridge University Press, |
| record_format | marc |
| spelling | Cristianini, Nello, author. http://id.loc.gov/authorities/names/nb99092565 An introduction to support vector machines : and other kernel-based learning methods / Nello Cristianini and John Shawe-Taylor. Cambridge ; New York : Cambridge University Press, [2000] 1 online resource (xiii, 189 pages) : illustrations (some color) text txt rdacontent computer c rdamedia online resource cr rdacarrier Includes bibliographical references (pages 173-186) and index. The learning methodology -- Linear learning machines -- Kernal-induced feature spaces -- Generalisation theory -- Optimisation theory -- Support vector machines -- Implementation techniques -- Application of support vector machines -- Pseudocode for the SMO algorithm -- Background mathematics. Description based on online resource; title from digital title page (Cambridge, viewed on June 5, 2024). "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."--Provided by publisher. English. Support vector machines. http://id.loc.gov/authorities/subjects/sh2008009003 Kernel functions. http://id.loc.gov/authorities/subjects/sh85072061 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Computer algorithms. http://id.loc.gov/authorities/subjects/sh91000149 Algorithms. http://id.loc.gov/authorities/subjects/sh85003487 Algorithms https://id.nlm.nih.gov/mesh/D000465 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage automatique. Algorithmes. Noyaux (Mathématiques) Machines à vecteurs supports. algorithms. aat COMPUTERS Enterprise Applications Business Intelligence Tools. bisacsh COMPUTERS Intelligence (AI) & Semantics. bisacsh Machine learning fast Computer algorithms fast Algorithms fast Kernel functions fast Support vector machines fast Maschinelles Lernen gnd Support-Vektor-Maschine gnd http://d-nb.info/gnd/4505517-8 Leerprocessen. gtt Generalisatie. gtt Optimaliseren. gtt Machine-learning. gtt Implementatie (dataverwerking) gtt Algoritmen. gtt Aprendizado computacional. larpcal Inteligência artificial. larpcal Intelligence artificielle. ram Apprentissage automatique. ram Acquisition des connaissances (systèmes experts) ram Modèles stochastiques d'apprentissage. ram Traitement vectoriel. ram Noyaux (analyse fonctionnelle) ram Algorithmes. ram Apprentissage automatique. rasuqam Algorithme. rasuqam Machine à vecteurs de support. rasuqam Noyau (Mathématiques) rasuqam Electronic book. Shawe-Taylor, John, author. http://id.loc.gov/authorities/names/n94058121 Print version: Cristianini, Nello. Introduction to support vector machines. Cambridge ; New York : Cambridge University Press, 2000 0521780195 (DLC) 99054716 (OCoLC)42753132 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=510940 Volltext |
| spellingShingle | Cristianini, Nello Shawe-Taylor, John An introduction to support vector machines : and other kernel-based learning methods / The learning methodology -- Linear learning machines -- Kernal-induced feature spaces -- Generalisation theory -- Optimisation theory -- Support vector machines -- Implementation techniques -- Application of support vector machines -- Pseudocode for the SMO algorithm -- Background mathematics. Support vector machines. http://id.loc.gov/authorities/subjects/sh2008009003 Kernel functions. http://id.loc.gov/authorities/subjects/sh85072061 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Computer algorithms. http://id.loc.gov/authorities/subjects/sh91000149 Algorithms. http://id.loc.gov/authorities/subjects/sh85003487 Algorithms https://id.nlm.nih.gov/mesh/D000465 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage automatique. Algorithmes. Noyaux (Mathématiques) Machines à vecteurs supports. algorithms. aat COMPUTERS Enterprise Applications Business Intelligence Tools. bisacsh COMPUTERS Intelligence (AI) & Semantics. bisacsh Machine learning fast Computer algorithms fast Algorithms fast Kernel functions fast Support vector machines fast Maschinelles Lernen gnd Support-Vektor-Maschine gnd http://d-nb.info/gnd/4505517-8 Leerprocessen. gtt Generalisatie. gtt Optimaliseren. gtt Machine-learning. gtt Implementatie (dataverwerking) gtt Algoritmen. gtt Aprendizado computacional. larpcal Inteligência artificial. larpcal Intelligence artificielle. ram Apprentissage automatique. ram Acquisition des connaissances (systèmes experts) ram Modèles stochastiques d'apprentissage. ram Traitement vectoriel. ram Noyaux (analyse fonctionnelle) ram Algorithmes. ram Apprentissage automatique. rasuqam Algorithme. rasuqam Machine à vecteurs de support. rasuqam Noyau (Mathématiques) rasuqam |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2008009003 http://id.loc.gov/authorities/subjects/sh85072061 http://id.loc.gov/authorities/subjects/sh85079324 http://id.loc.gov/authorities/subjects/sh91000149 http://id.loc.gov/authorities/subjects/sh85003487 https://id.nlm.nih.gov/mesh/D000465 https://id.nlm.nih.gov/mesh/D000069550 http://d-nb.info/gnd/4505517-8 |
| title | An introduction to support vector machines : and 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 | introduction to support vector machines and other kernel based learning methods |
| title_sub | and other kernel-based learning methods / |
| topic | Support vector machines. http://id.loc.gov/authorities/subjects/sh2008009003 Kernel functions. http://id.loc.gov/authorities/subjects/sh85072061 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Computer algorithms. http://id.loc.gov/authorities/subjects/sh91000149 Algorithms. http://id.loc.gov/authorities/subjects/sh85003487 Algorithms https://id.nlm.nih.gov/mesh/D000465 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage automatique. Algorithmes. Noyaux (Mathématiques) Machines à vecteurs supports. algorithms. aat COMPUTERS Enterprise Applications Business Intelligence Tools. bisacsh COMPUTERS Intelligence (AI) & Semantics. bisacsh Machine learning fast Computer algorithms fast Algorithms fast Kernel functions fast Support vector machines fast Maschinelles Lernen gnd Support-Vektor-Maschine gnd http://d-nb.info/gnd/4505517-8 Leerprocessen. gtt Generalisatie. gtt Optimaliseren. gtt Machine-learning. gtt Implementatie (dataverwerking) gtt Algoritmen. gtt Aprendizado computacional. larpcal Inteligência artificial. larpcal Intelligence artificielle. ram Apprentissage automatique. ram Acquisition des connaissances (systèmes experts) ram Modèles stochastiques d'apprentissage. ram Traitement vectoriel. ram Noyaux (analyse fonctionnelle) ram Algorithmes. ram Apprentissage automatique. rasuqam Algorithme. rasuqam Machine à vecteurs de support. rasuqam Noyau (Mathématiques) rasuqam |
| topic_facet | Support vector machines. Kernel functions. Machine learning. Computer algorithms. Algorithms. Algorithms Machine Learning Apprentissage automatique. Algorithmes. Noyaux (Mathématiques) Machines à vecteurs supports. algorithms. COMPUTERS Enterprise Applications Business Intelligence Tools. COMPUTERS Intelligence (AI) & Semantics. Machine learning Computer algorithms Kernel functions Support vector machines Maschinelles Lernen Support-Vektor-Maschine Leerprocessen. Generalisatie. Optimaliseren. Machine-learning. Implementatie (dataverwerking) Algoritmen. Aprendizado computacional. Inteligência artificial. Intelligence artificielle. Acquisition des connaissances (systèmes experts) Modèles stochastiques d'apprentissage. Traitement vectoriel. Noyaux (analyse fonctionnelle) Algorithme. Machine à vecteurs de support. Noyau (Mathématiques) Electronic book. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=510940 |
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