An elementary introduction to statistical learning theory

"A joint endeavor from leading researchers in the fields of philosophy and electrical engineering An Introduction to Statistical Learning Theory provides a broad and accessible introduction to rapidly evolving field of statistical pattern recognition and statistical learning theory. Exploring t...

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Detalles Bibliográficos
Autor principal: Kulkarni, Sanjeev (-)
Autor Corporativo: Wiley InterScience (Online service) (-)
Otros Autores: Harman, Gilbert
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, N.J. : Wiley 2011.
Colección:EBSCO Academic eBook Collection Complete.
Wiley series in probability and statistics.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b3111703x*spi
Descripción
Sumario:"A joint endeavor from leading researchers in the fields of philosophy and electrical engineering An Introduction to Statistical Learning Theory provides a broad and accessible introduction to rapidly evolving field of statistical pattern recognition and statistical learning theory. Exploring topics that are not often covered in introductory level books on statistical learning theory, including PAC learning, VC dimension, and simplicity, the authors present upper-undergraduate and graduate levels with the basic theory behind contemporary machine learning and uniquely suggest it serves as an excellent framework for philosophical thinking about inductive inference"--Back cover.
Formato:Forma de acceso: World Wide Web.
Bibliografía:Incluye referencias bibliográficas e índice.
ISBN:9781118023471
9781118023433
9781283098687