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Learning from data : concepts, theory, and methods / / Vladimir Cherkassky, Filip Mulier
| Learning from data : concepts, theory, and methods / / Vladimir Cherkassky, Filip Mulier |
| Autore | Cherkassky Vladimir S |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : IEEE Press : , c2007 |
| Descrizione fisica | 1 online resource (558 p.) |
| Disciplina |
006.31
006.32 |
| Altri autori (Persone) | MulierFilip |
| Soggetto topico |
Adaptive signal processing
Machine learning Neural networks (Computer science) Fuzzy systems |
| ISBN |
1-281-00188-0
9786611001889 0-470-14052-6 0-470-14051-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Problem statement, classical approaches, and adaptive learning -- Regularization framework -- Statistical learning theory -- Nonlinear optimization strategies -- Methods for data reduction and dimensionality reduction -- Methods for regression -- Classification -- Support vector machines -- Noninductive inference and alternative learning formulations. |
| Record Nr. | UNISA-996215456703316 |
Cherkassky Vladimir S
|
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| Hoboken, New Jersey : , : IEEE Press : , c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Learning from data : concepts, theory, and methods / / Vladimir Cherkassky, Filip Mulier
| Learning from data : concepts, theory, and methods / / Vladimir Cherkassky, Filip Mulier |
| Autore | Cherkassky Vladimir S |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : IEEE Press, : Wiley-Interscience, c2007 |
| Descrizione fisica | 1 online resource (558 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) | MulierFilip |
| Soggetto topico |
Adaptive signal processing
Machine learning Neural networks (Computer science) Fuzzy systems |
| ISBN |
1-281-00188-0
9786611001889 0-470-14052-6 0-470-14051-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Problem statement, classical approaches, and adaptive learning -- Regularization framework -- Statistical learning theory -- Nonlinear optimization strategies -- Methods for data reduction and dimensionality reduction -- Methods for regression -- Classification -- Support vector machines -- Noninductive inference and alternative learning formulations. |
| Record Nr. | UNINA-9910144576703321 |
|
Cherkassky Vladimir S
|
||
| Hoboken, N.J., : IEEE Press, : Wiley-Interscience, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||