Kernel methods for pattern analysis / / John Shawe-Taylor, Nello Cristianini [[electronic resource]] |
Autore | Shawe-Taylor John |
Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2004 |
Descrizione fisica | 1 online resource (xiv, 462 pages) : digital, PDF file(s) |
Disciplina | 006.3/1 |
Soggetto topico |
Machine learning
Algorithms Kernel functions Pattern perception - Data processing |
ISBN |
1-107-14456-6
1-139-63694-4 1-280-51598-8 9786610515981 0-511-21418-9 0-511-21597-5 0-511-21060-4 0-511-31495-7 0-511-80968-9 0-511-21237-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Cover; Half-title; Title; Copyright; Contents; Code fragments; Preface; 1 Pattern analysis; 2 Kernel methods: an overview; 3 Properties of kernels; 4 Detecting stable patterns; 5 Elementary algorithms in feature space; 6 Pattern analysis using eigen-decompositions; 7 Pattern analysis using convex optimisation; 8 Ranking, clustering and data visualisation; 9 Basic kernels and kernel types; 10 Kernels for text; 11 Kernels for structured data: strings, trees, etc.; 12 Kernels from generative models; Appendix A Proofs omitted from the main text; A.1 Proof of McDiarmid's theorem
A.2 Stability of principal components analysisA.3 Proofs of diffusion kernels; Appendix B Notational conventions; B.1 List of symbols; B.2 Notation for Tables; Appendix C List of pattern analysis methods; C.1 Pattern analysis computations; C.2 Pattern analysis algorithms; Appendix D List of kernels; D.1 Kernel definitions and computations; D.2 Kernel algorithms; References; Index |
Record Nr. | UNINA-9910457168903321 |
Shawe-Taylor John
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Cambridge : , : Cambridge University Press, , 2004 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
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Kernel methods for pattern analysis / / John Shawe-Taylor, Nello Cristianini [[electronic resource]] |
Autore | Shawe-Taylor John |
Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2004 |
Descrizione fisica | 1 online resource (xiv, 462 pages) : digital, PDF file(s) |
Disciplina | 006.3/1 |
Soggetto topico |
Machine learning
Algorithms Kernel functions Pattern perception - Data processing |
ISBN |
1-107-14456-6
1-139-63694-4 1-280-51598-8 9786610515981 0-511-21418-9 0-511-21597-5 0-511-21060-4 0-511-31495-7 0-511-80968-9 0-511-21237-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Cover; Half-title; Title; Copyright; Contents; Code fragments; Preface; 1 Pattern analysis; 2 Kernel methods: an overview; 3 Properties of kernels; 4 Detecting stable patterns; 5 Elementary algorithms in feature space; 6 Pattern analysis using eigen-decompositions; 7 Pattern analysis using convex optimisation; 8 Ranking, clustering and data visualisation; 9 Basic kernels and kernel types; 10 Kernels for text; 11 Kernels for structured data: strings, trees, etc.; 12 Kernels from generative models; Appendix A Proofs omitted from the main text; A.1 Proof of McDiarmid's theorem
A.2 Stability of principal components analysisA.3 Proofs of diffusion kernels; Appendix B Notational conventions; B.1 List of symbols; B.2 Notation for Tables; Appendix C List of pattern analysis methods; C.1 Pattern analysis computations; C.2 Pattern analysis algorithms; Appendix D List of kernels; D.1 Kernel definitions and computations; D.2 Kernel algorithms; References; Index |
Record Nr. | UNINA-9910784411103321 |
Shawe-Taylor John
![]() |
||
Cambridge : , : Cambridge University Press, , 2004 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Kernel methods for pattern analysis / / John Shawe-Taylor, Nello Cristianini |
Autore | Shawe-Taylor John |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Cambridge, UK ; ; New York, : Cambridge University Press, 2004 |
Descrizione fisica | 1 online resource (xiv, 462 pages) : digital, PDF file(s) |
Disciplina | 006.3/1 |
Altri autori (Persone) | CristianiniNello |
Soggetto topico |
Machine learning
Algorithms Kernel functions Pattern perception - Data processing |
ISBN |
1-107-14456-6
1-139-63694-4 1-280-51598-8 9786610515981 0-511-21418-9 0-511-21597-5 0-511-21060-4 0-511-31495-7 0-511-80968-9 0-511-21237-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Cover; Half-title; Title; Copyright; Contents; Code fragments; Preface; 1 Pattern analysis; 2 Kernel methods: an overview; 3 Properties of kernels; 4 Detecting stable patterns; 5 Elementary algorithms in feature space; 6 Pattern analysis using eigen-decompositions; 7 Pattern analysis using convex optimisation; 8 Ranking, clustering and data visualisation; 9 Basic kernels and kernel types; 10 Kernels for text; 11 Kernels for structured data: strings, trees, etc.; 12 Kernels from generative models; Appendix A Proofs omitted from the main text; A.1 Proof of McDiarmid's theorem
A.2 Stability of principal components analysisA.3 Proofs of diffusion kernels; Appendix B Notational conventions; B.1 List of symbols; B.2 Notation for Tables; Appendix C List of pattern analysis methods; C.1 Pattern analysis computations; C.2 Pattern analysis algorithms; Appendix D List of kernels; D.1 Kernel definitions and computations; D.2 Kernel algorithms; References; Index |
Record Nr. | UNINA-9910825792703321 |
Shawe-Taylor John
![]() |
||
Cambridge, UK ; ; New York, : Cambridge University Press, 2004 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II / / edited by Peter A. Flach, Tijl De Bie, Nello Cristianini |
Edizione | [1st ed. 2012.] |
Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 |
Descrizione fisica | 1 online resource (XXVI, 867 p. 245 illus.) |
Disciplina | 006.312 |
Collana | Lecture Notes in Artificial Intelligence |
Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Computer science—Mathematics Mathematical statistics Information storage and retrieval Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Discrete Mathematics in Computer Science Probability and Statistics in Computer Science Information Storage and Retrieval |
ISBN | 3-642-33486-5 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Privacy and security -- rankings and recommendations -- reinforcement learning and planning -- rule mining and subgroup discovery -- semi-supervised and transductive learning -- sensor data -- sequence and string mining -- social network mining -- spatial and geographical data mining -- statistical methods and evaluation -- time series and temporal data mining -- transfer learning. |
Record Nr. | UNISA-996465590203316 |
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part I / / edited by Peter A. Flach, Tijl De Bie, Nello Cristianini |
Edizione | [1st ed. 2012.] |
Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 |
Descrizione fisica | 1 online resource (XXVI, 879 p. 241 illus.) |
Disciplina | 006.312 |
Collana | Lecture Notes in Artificial Intelligence |
Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Computer science—Mathematics Mathematical statistics Information storage and retrieval Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Discrete Mathematics in Computer Science Probability and Statistics in Computer Science Information Storage and Retrieval |
ISBN | 3-642-33460-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Aassociation rules and frequent patterns -- Bayesian learning and graphical models -- classification -- dimensionality reduction, feature selection and extraction -- distance-based methods and kernels -- ensemble methods -- graph and tree mining -- large-scale, distributed and parallel mining and learning -- multi-relational mining and learning -- multi-task learning -- natural language processing -- online learning and data streams. |
Record Nr. | UNISA-996465591703316 |
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 | ||
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Lo trovi qui: Univ. di Salerno | ||
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